Debian Med Project
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Summary
Biology
Debian Med - Pakete für Mikrobiologie

Dieses Metapaket wird Debian-Pakete mit Bezug zu Molekularbiologie, Strukturbiologie und Bioinformatik für den Einsatz in den Biowissenschaften installieren.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Med to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Med mailing list

Links to other tasks

Debian Med Biology packages

Official Debian packages with high relevance

Abacas
close gaps in genomic alignments from short reads
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ABACAS (Algorithm Based Automatic Contiguation of Assembled Sequences) intends to rapidly contiguate (align, order, orientate), visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence.

ABACAS uses MUMmer to find alignment positions and identify syntenies of assembled contigs against the reference. The output is then processed to generate a pseudomolecule taking overlapping contigs and gaps in to account. ABACAS generates a comparison file that can be used to visualize ordered and oriented contigs in ACT. Synteny is represented by red bars where colour intensity decreases with lower values of percent identity between comparable blocks. Information on contigs such as the orientation, percent identity, coverage and overlap with other contigs can also be visualized by loading the outputted feature file on ACT.

Please cite: Samuel Assefa, Thomas M. Keane, Thomas D. Otto, Chris Newbold and Matthew Berriman: ABACAS: algorithm-based automatic contiguation of assembled sequences. (PubMed,eprint) Bioinformatics 25(15):1968-1969 (2009)
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Abyss
de novo, parallel, sequence assembler for short reads
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ABySS is a de novo, parallel, sequence assembler that is designed for short reads. It may be used to assemble genome or transcriptome sequence data. Parallelization is achieved using MPI, OpenMP and pthread.

Please cite: Jared T. Simpson, Kim Wong, Shaun D. Jackman, Jacqueline E. Schein, Steven J.M. Jones and İnanç Birol: ABySS: A parallel assembler for short read sequence data. (PubMed,eprint) Genome Research 19(6):1117-23 (2009)
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Acedb-other
Abrufen von DNA- oder Proteinsequenzen
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Dieses Paket vereint alle kleinen Anwendungen die acedb unter dem Ziel »other« seines Makefiles sammelt.

Efetch: vermutlich kurz für: »entry fetch« (Eintrag abrufen), sammelt Sequenzinformationen von bekannten DNA- und Proteindatenbanken.

Please cite: L. D. Stein and J. Thierry-Mieg: AceDB: a genome database management system. Computing in Science and Engineering 1(3):44-52 (1999)
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Adapterremoval
rapid adapter trimming, identification, and read merging of gene sequences
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This program searches for and removes remnant adapter sequences from High- Throughput Sequencing (HTS) data and (optionally) trims low quality bases from the 3' end of reads following adapter removal. AdapterRemoval can analyze both single end and paired end data, and can be used to merge overlapping paired-ended reads into (longer) consensus sequences. Additionally, the AdapterRemoval may be used to recover a consensus adapter sequence for paired-ended data, for which this information is not available.

Please cite: Mikkel Schubert, Stinus Lindgreen and Ludovic Orlando: AdapterRemoval v2: rapid adapter trimming, identification, and read merging. (PubMed,eprint) BMC Research Notes 9:88 (2016)
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Adun-core
Molekularsimulator
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Adun ist ein Simulator für Biomoleküle, der zusätzlich die Fähigkeiten für Datenverwaltung und -analyse mitbringt. Adun wurde am »Computational Biophysics and Biochemistry Laboratory«, einem Teil der »Research Unit on Biomedical Informatics« der UPF entwickelt.

Dieses Paket enthält das Program AdunCore und den Adun-Server. Wenn Sie eine grafische Benutzeroberfläche wünschen, installieren Sie das Paket adun.app.

Please cite: Michael A. Johnston, Ignacio Fdez. Galván and Jordi Villà-Freixa: Framework-based design of a new all-purpose molecular simulation application: The Adun simulator. (PubMed) J. Comp. Chem. 26(15):1647-1659 (2005)
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Aegean
integrated genome analysis toolkit
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The AEGeAn Toolkit is designed for the Analysis and Evaluation of Genome Annotations. The toolkit includes a variety of analysis programs, e.g. for comparing distinct sets of gene structure annotations (ParsEval), computation of gene loci (LocusPocus) and more.

Please cite: Daniel S Standage and Volker P Brendel: ParsEval: parallel comparison and analysis of gene structure annotations.. (PubMed,eprint) BMC Bioinformatics 13(1):187 (2012)
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Aevol
Digitales genetisches Modell zur Durchführung von Evolutionsexperimenten in silico
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Aevol ist ein digitales genetisches Modell: Populationen digitaler Organismen werden einem Prozess von Selektion und Variation ausgesetzt, wodurch eine darwinsche Dynamik entsteht.

Durch Modifikation der Selektionsfaktoren (z.B. Populationsgröße, Art der Umgebung, Variation der Umwelt) oder der Variationsfaktoren (z.B. Mutationsraten, Chromosomenveränderungsraten, Arten der Veränderung, horizontale Transfers) kann experimentell der Einfluss dieser Parameter auf die Struktur der sich entwickelnden Organismen untersucht werden. Insbesondere, da Aevol ein präzises und realistisches Modell des Erbgutes (Genom) enthält, ermöglicht es die Untersuchung struktureller Variationen des Genoms (z.B. Anzahl der Gene, Syntenie, Anteil codierender Sequenzen).

Die Simulationsplattform beinhaltet eine Sammlung von Werkzeugen zur Analyse der Phylogenien und zur Erfassung unterschiedlicher Eigenschaften der Organismen und Populationen während der Evolution.

Please cite: Dusan Misevic, Antoine Frenoy, David P. Parsons and Francois Taddei: Effects of public good properties on the evolution of cooperation. (eprint) :218-225 (2012)
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Alien-hunter
Interpolated Variable Order Motifs zur Identifizierung horizontal erhaltener DNA
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Die Anwendung alien_hunter sagt vermutlichen Horizontalen Gentransfer (HGT) mit der Implementierung der Interpolated Variable Order Motifs (IVOMs) voraus. Ein IVOM-Ansatz nutzt ergänzende Tendenzen mittels variablen Anordnungen von Sequenzmotiv-Verteilungen und entdeckt verlässlicher die lokale Zusammenstellung einer Sequenz verglichen mit Methoden mit fester Anordnung. Optional können Voraussagen überführt werden in ein Hidden Markov Model (HMM) zweiter Ordnung mit zwei Zuständen, um die Lokalisierung der Grenzen der vorausgesagten Regionen zu optimieren. Die Voraussagen (embl-Format) können automatisch in den Genombetrachter Artemis geladen werden. Er ist frei unter http://www.sanger.ac.uk/Software/Artemis/ verfügbar.

Please cite: Georgios S. Vernikos and Julian Parkhill: Interpolated variable order motifs for identification of horizontally acquired DNA: revisiting the Salmonella pathogenicity islands. (PubMed,eprint) Bioinformatics 22(18):2196-2203 (2006)
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Alter-sequence-alignment
Umgebung zur Umwandlung von Aligments genomischer Sequenzen
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Das Werkzeug ALTER (ALignment Transformation EnviRonment) wandelt zwischen Formaten für multiple Sequenzalignments um. ALTER fokussiert sich auf die Spezifikationen der gebräuchlichsten Alignment- und Analyseprogramme anstatt auf die Umwandlung zwischen mehr oder weniger speziellen Formaten.

Please cite: Daniel Glez-Peña, Daniel Gómez-Blanco, Miguel Reboiro-Jato, Florentino Fdez-Riverola and David Posada: ALTER: program-oriented conversion of DNA and protein alignments". (PubMed,eprint) Nucl. Acids Res. 38(suppl 2):W14-W18 (2010)
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Altree
Programm zur Phylogenie-basierten Assoziations- und Lokalisierungsanalyse
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ALTree wurde für entworfen, um Assoziationen zu entdecken und Suszeptibilitäts-Lokuse (susceptibility loci) mittels phylogenetischen Bäumen aus Haplotypen zu lokalisieren. Zum Einen ermöglicht sie die Entdeckung einer Assoziation zwischen einem untersuchten Gen und einer Krankheit, zum Anderen wird eine Hypothese über Suszeptibilitäts-Lokuse möglich.

Please cite: Claire Bardel, Vincent Danjean and Emmanuelle Genin: ALTree: association detection and localization of susceptibility sites using haplotype phylogenetic trees. (PubMed,eprint) Bioinformatics 22(11):1402-1403 (2006)
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Amap-align
Protein multiple alignment by sequence annealing
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AMAP is a command line tool to perform multiple alignment of peptidic sequences. It utilizes posterior decoding, and a sequence-annealing alignment, instead of the traditional progressive alignment method. It is the only alignment program that allows one to control the sensitivity / specificity tradeoff. It is based on the ProbCons source code, but uses alignment metric accuracy and eliminates the consistency transformation.

The Java visualisation tool of AMAP 2.2 is not yet packaged in Debian.

Please cite: Ariel S. Schwartz and Lior Pachter: Multiple alignment by sequence annealing. (eprint) Bioinformatics 23(2):e24-e29 (2007)
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Remark of Debian Med team: Dead upstream

The homepage of this project vanished as well as the Download area. An old unmaintained version remained at code.google.com. Please drop the maintainer a note if you have any news of this project.

Ampliconnoise
removal of noise from 454 sequenced PCR amplicons
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AmpliconNoise is a package of applications to clean up high-throughput sequence data. It consists of three main parts:

Pyronoise - does flowgram-based clustering to spot misreads SeqNoise - removes PCR point mutations Perseus - removes PCR chimeras without the need for a set of reference sequences

Previously there was a standalone "Pyronoise" by the same authors and this package includes an updated version. There is also a "Denoiser" in Qiime which is related but distinct.

Please cite: Christopher Quince, Anders Lanzen, Russell J Davenport and Peter J Turnbaugh: Removing Noise From Pyrosequenced Amplicons. (PubMed,eprint) BMC Bioinformatics 12:38 (2011)
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Andi
Efficient Estimation of Evolutionary Distances
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This is the andi program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because andi does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.

Please cite: Bernhard Haubold, Fabian Klötzl and Peter Pfaffelhuber: andi: Fast and accurate estimation of evolutionary distances between closely related genomes. (PubMed,eprint) Bioinformatics 31(8):1169-1175 (2015)
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Anfo
Alignments/Abbildungen kurzer DNA-Sequenzen, von MPG
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Anfo ist ein Mapper in der Art von Soap/Maq/Bowtie, aber die Implementierung ähnelt eher BLAST/BLAT. Anful ist für Alignments sequenzierter Reads (kurze DNA-Sequenzen) am nützlichsten, wenn die DNA-Sequenz irgendwie verändert wurde (etwa sehr alte DNA oder Bisulfit-Behandlung) und/oder wenn es zwischen Probe und Referenz mehr Abweichungen gibt, als schnelle Mapper problemlos vertragen (etwa wenn das Referenzgenom fehlt und stattdessen eine verwandte Spezies benutzt wird).

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Aragorn
tRNA- und tmRNA-Nachweis in Nukleotidsequenzen
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Das Programm verwendet heuristische Algorithmen zur Vorhersage von tRNA-Sekundärstruktur, basierend auf der Homologie mit erkannten tRNA-Konsensus-Sequenzen und der Fähigkeit zur Bildung einer basengepaarten Kleeblattstruktur. tmRNA-Gene werden mittels einer modifizierten Version des BRUCE-Programms identifiziert.

Please cite: Dean Laslett and Bjorn Canback: ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. (PubMed,eprint) Nucleic Acids Research 32(1):11-16 (2004)
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Arden
specificity control for read alignments using an artificial reference
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ARDEN (Artificial Reference Driven Estimation of false positives in NGS data) is a novel benchmark that estimates error rates based on real experimental reads and an additionally generated artificial reference genome. It allows the computation of error rates specifically for a dataset and the construction of a ROC-curve. Thereby, it can be used to optimize parameters for read mappers, to select read mappers for a specific problem or also to filter alignments based on quality estimation.

Please cite: Sven H. Giese, Franziska Zickmann and Bernhard Y. Renard: Specificity control for read alignments using an artificial reference genome-guided false discovery rate. (PubMed,eprint) Bioinformatics 30(1):9-16 (2013)
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Ariba
Antibiotic Resistance Identification By Assembly
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ARIBA is a tool that identifies antibiotic resistance genes by running local assemblies. The input is a FASTA file of reference genes and paired sequencing reads. ARIBA reports which of the reference genes were found, plus detailed information on the quality of the assemblies and any variants between the sequencing reads and the reference genes.

Please cite: Martin Hunt, Alison E. Mather, Leonor Sanchez-Buso, Andrew J. Page, Julian Parkhill, Jacqueline A. Keane and Simon R. Harris: ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. (PubMed,eprint) Microbial Genomics 3 (2017)
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Art-nextgen-simulation-tools
simulation tools to generate synthetic next-generation sequencing reads
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ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Please cite: Weichun Huang, Leping Li, Jason R. Myers and Gabor T. Marth: ART: a next-generation sequencing read simulator. (PubMed,eprint) Bioinformatics 28(4):593-594 (2012)
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Artemis
genome browser and annotation tool
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Artemis is a genome browser and annotation tool that allows visualisation of sequence features, next generation data and the results of analyses within the context of the sequence, and also its six-frame translation.

This package includes the Artemis genome browser, the Artemis Comparison Tool (ACT), and the DNAplotter and BamView utilities.

Please cite: Tim Carver, Simon R. Harris, Matthew Berriman, Julian Parkhill and Jacqueline A. McQuillan: Artemis: an integrated platform for visualization and analysis of high-throughput sequence-based experimental data. (PubMed,eprint) Bioinformatics 28(4):464-469 (2012)
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Artfastqgenerator
outputs artificial FASTQ files derived from a reference genome
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ArtificialFastqGenerator takes the reference genome (in FASTA format) as input and outputs artificial FASTQ files in the Sanger format. It can accept Phred base quality scores from existing FASTQ files, and use them to simulate sequencing errors. Since the artificial FASTQs are derived from the reference genome, the reference genome provides a gold-standard for calling variants (Single Nucleotide Polymorphisms (SNPs) and insertions and deletions (indels)). This enables evaluation of a Next Generation Sequencing (NGS) analysis pipeline which aligns reads to the reference genome and then calls the variants.

Please cite: Matthew Frampton and Richard Houlston: Generation of Artificial FASTQ Files to Evaluate the Performance of Next-Generation Sequencing Pipelines. (PubMed,eprint) PLOSone 7(11):e49110 (2012)
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Assemblytics
detect and analyze structural variants from a genome assembly
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Assemblytics incorporates a unique anchor filtering approach to increase robustness to repetitive elements, and identifies six classes of variants based on their distinct alignment signatures. Assemblytics can be applied both to comparing aberrant genomes, such as human cancers, to a reference, or to identify differences between related species.

Please cite: Maria Nattestad and Michael C. Schatz: Assemblytics: a web analytics tool for the detection of variants from an assembly. (PubMed) Bioinformatics 32(19):3021-3023 (2016)
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Atac
genome assembly-to-assembly comparison
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atac computes a one-to-one pairwise alignment of large DNA sequences. It first finds the unique k-mers in each sequence, chains them to larger blocks, and fills in spaces between blocks. It was written primarily to transfer annotations between different assemblies of the human genome.

The output is a set of ungapped 'matches', and a set of gapped 'runs' formed from the matches. Each match or run associates one sequence with the other sequence. The association is 'unique', in that there is no other (sizeable) associations for either sequence. Thus, large repeats and duplications are not present in the output - they appear as unmapped regions.

Though the output is always pairwise, atac can cache intermediate results to speed a comparisons of multiple sequences.

This package is part of the Kmer suite.

The package is enhanced by the following packages: kmer-examples
Please cite: B. Walenz and L. Florea: Sim4db and leaff: Utilities for fast batched spliced alignment and sequence indexing. (PubMed) Bioinformatics 27(13):1869-1870 (2011)
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Augustus
gene prediction in eukaryotic genomes
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AUGUSTUS is a software for gene prediction in eukaryotic genomic sequences that is based on a generalized hidden Markov model (HMM), a probabilistic model of a sequence and its gene structure. After learning gene structures from a reference annotation, AUGUSTUS uses the HMM to recognize genes in a new sequence and annotates it with the regions of identified genes. External hints, e.g. from RNA sequencing, EST or protein alignments etc. can be used to guide and improve the gene finding process. The result is the set of most likely gene structures that comply with all given user constraints, if such gene structures exist. AUGUSTUS already includes prebuilt HMMs for many species, as well as scripts to train custom models using annotated genomes.

Please cite: M. Stanke, O. Schöffmann, B. Morgenstern and S. Waack: Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. (PubMed,eprint) BMC Bioinformatics 7:62 (2006)
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Autodock
Analyse der Ligandenbindung von Proteinstrukturen
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AutoDock ist ein erstklassiger Vertreter von Programmen zur Simulation einer Bindung relativ kleiner Liganden an verhältnismäßig große Rezeptor-Proteine. In vorhergehenden Versionen waren die Liganden sehr flexibel, während das Protein dagegen sehr starr behandelt wurde. Die aktuelle Version 4 erweitert die Flexibilität auf ausgewählte Seitenketten an der Oberfläche des Proteins, berücksichtigt also auch Rotamere.

AutoDock vollzieht die Bindung des Liganden an einer Auswahl von Gittern, die das Zielprotein beschreiben. AutoGrid berechnet diese Gitter vorab.

The package is enhanced by the following packages: autogrid
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Autodock-vina
Docking kleiner Moleküle an Proteine
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Das Programm AutoDock Vina unterstützt die Pharmaforschung, molekulares Docking und virtuelles Screening von Molekülbibliotheken. Es bietet Mehrkernunterstützung, hohe Leistung, verbesserte Genauigkeit und einfache Benutzung.

Dasselbe Institut hat das weitverbreitete autodock entwickelt.

O. Trott, A. J. Olson, AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading, Journal of Computational Chemistry 31 (2010) 455-461

Please cite: Oleg Trott and Arthur J. Olson: AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. (eprint) Journal of Computational Chemistry 31(2):455-461 (2010)
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Autogrid
Vorberechnung der Bindung von Liganden an ihren Rezeptor
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Die AutoDockSuite dient der molekularen Analyse der Anheftung von kleinen, chemischen Komponenten an ihre Rezeptoren mit bekannter, dreidimensionaler Struktur.

Das AutoGrid-Programm führt Vorberechnungen zur Anheftung eines Liganden an einen Gittersatz durch, welche den Effekt von Punktladungen an Proteinen beschreiben. Der Effekt dieser Kräfte auf den Liganden wird dann durch das AutoDock-Programm analysiert.

Avogadro
System für Molekülgrafiken und -modellierung
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Avogadro ist ein System für Molekülgrafiken und -modellierung, das für Moleküle und Biomoleküle gedacht ist. Es kann Eigenschaften wie Molekülorbitale oder elektrostatische Potentiale visualisieren und enthält einen intuitiven Moleküleditor.

Es verfügt über die folgenden Fähigkeiten:

  • Molekülmodellierer mit automatischer kraftfeldbasierter Geometrie-Optimierung
  • Molekülmechanik einschließlich der Suche mit Bedingungen und Conformern
  • Visualisierung von Molekülorbitalen und allgemeinen Isoflächen
  • Visualisierung von Schwingungen und Darstellung von Schwingungsspektren
  • Unterstützung von kristallografischen Einheitszellen
  • Eingabeerzeugung für die quantenchemischen Pakete Gaussian, GAMESS und MOLPRO
  • Flexible Erweiterungsarchitektur und Python-Skripting

Avogadro kann die Dateiformate PDB, XYZ, CML, CIF und Molden sowie die Ausgabe von Gaussian, GAMESS und MOLPRO lesen.

Please cite: Marcus D Hanwell, Donald E Curtis, David C Lonie, Tim Vandermeersch, Eva Zurek and Geoffrey R Hutchison: Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. (eprint) J. Cheminf. 4:17 (2012)
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Axe-demultiplexer
Trie-based DNA sequencing read demultiplexer
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Axe very rapidly selects the optimal barcode present in a sequence read, even in the presence of sequencing errors. The algorithm is able to handle combinatorial barcoding, barcodes of differing length, and several mismatches per barcode.

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Baitfisher
software package for designing hybrid enrichment probes
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The BaitFisher package consists of two programs: BaitFisher and BaitFilter.

BaitFisher was been designed to construct hybrid enrichment baits from multiple sequence alignments (MSAs) or annotated features in MSAs. The main goal of BaitFisher is to avoid redundancy in the construction of baits by designing fewer baits in conserved regions of the MSAs and designing more baits in variable regions. This makes use of the fact that hybrid enrichment baits can differ to some extends from the target region, which they should capture in the enrichment procedure. By specifying the allowed distance between baits and the sequences in the MSAs the user can control the allowed bait-to-target distance and the degree of reduction in the number of baits that are designed. See the BaitFisher paper for details.

BaitFilter was designed (i) to determine whether baits bind unspecifically to a reference genome, (ii) to filter baits that only have partial length matches to a reference genome, (iii) to determine the optimal bait region in a MSA and to convert baits to a format that can be uploaded at a bait constructing company. The optimal bait region can be the most conserved region in the MSA or the region with the highest number of sequences without gaps or ambiguous nucleotides.

Please cite: Christoph Mayer, Manuela Sann, Alexander Donath, Martin Meixner, Lars Podsiadlowski, Ralph S. Peters, Malte Petersen, Karen Meusemann, Karsten Liere, Johann-Wolfgang Wägele, Bernhard Misof, Christoph Bleidorn, Michael Ohl and Oliver Niehuis: BaitFisher: A Software Package for Multispecies Target DNA Enrichment Probe Design. (PubMed,eprint) Mol. Biol. Evol. 33(7):1875-1886 (2016)
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Bali-phy
Bayesian Inference of Alignment and Phylogeny
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BAli-Phy estimates multiple sequence alignments and evolutionary trees from unaligned DNA, amino acid, or codon sequences. BAli-Phy uses MCMC to estimate evolutionary trees, positive selection, and branch lengths while averaging over alternative alignments. BAli-Phy can display alignment ambiguity graphically in an alignment uncertainty (AU) plot.

BAli-Phy can also estimate phylogenies from a fixed alignment (like MrBayes and BEAST) using substitution models like GTR+gamma. BAli-Phy automatically estimates relative rates for each gene.

Please cite: Benjamin D. Redelings and Marc A. Suchard: Joint Bayesian Estimation of Alignment and Phylogeny. (PubMed,eprint) Systematic Biology 54(3):401-418 (2005)
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Ballview
Freies Werkzeug für Molekulardesign und -grafiken
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BALLView bietet eine schnelle OpenGL-basierte Visualisierung von Molekülstrukturen, molekularmechanische Methoden (Minimierung, MD-Simulation mittels AMBER-, CHARMM- und MMFF93-Kraftfeldern), Berechnung und Darstellung von elektrostatischen Eigenschaften (FDPB) und Funktionen zum Bearbeiten von Molekülen.

BALLView kann als grafische Benutzerschnittstelle angesehen werden, deren Grundlage BALL (Biochemical Algorithms Library) ist. BALL konzentriert sich auf die gebräuchlichsten Forderungen von Proteinchemikern und Biophysikern. BALLView wird derzeit von den Gruppen um Hans-Peter Lenhof (Universität des Saarlandes, Saarbrücken, Deutschland) und Oliver Kohlbacher (Eberhard Karls Universität Tübingen, Deutschland) entwickelt. BALL ist ein Anwendungsrahmenwerk in C++, das speziell für schnelle Softwareentwicklung in Moleküldesign und computerunterstützter Molekularbiologie entwickelt wurde. Es liefert einen umfangreichen Satz an Datenstrukturen, Klassen für Molekülmechaniken, fortgeschrittene Lösungsmethoden, Vergleich und Analyse von Proteinstrukturen, Dateiimport/-export und Visualisierung.

Please cite: Andreas Moll, Andreas Hildebrandt, Hans-Peter Lenhof and Oliver Kohlbacher: BALLView: a tool for research and education in molecular modeling. (PubMed,eprint) Bioinformatics 22(3):365-366 (2006)
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Bamtools
toolkit for manipulating BAM (genome alignment) files
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BamTools facilitates research analysis and data management using BAM files. It copes with the enormous amount of data produced by current sequencing technologies that is typically stored in compressed, binary formats that are not easily handled by the text-based parsers commonly used in bioinformatics research.

BamTools provides both a C++ API for BAM file support as well as a command-line toolkit.

This is the bamtools command-line toolkit.

Available bamtools commands:

 convert  Converts between BAM and a number of other formats
 count    Prints number of alignments in BAM file(s)
 coverage Prints coverage statistics from the input BAM file
 filter   Filters BAM file(s) by user-specified criteria
 header   Prints BAM header information
 index    Generates index for BAM file
 merge    Merge multiple BAM files into single file
 random   Select random alignments from existing BAM file(s), intended more
          as a testing tool.
 resolve  Resolves paired-end reads (marking the IsProperPair flag as needed)
 revert   Removes duplicate marks and restores original base qualities
 sort     Sorts the BAM file according to some criteria
 split    Splits a BAM file on user-specified property, creating a new BAM
          output file for each value found
 stats    Prints some basic statistics from input BAM file(s)
Please cite: Derek W. Barnett, Erik K. Garrison, Aaron R. Quinlan, Michael P. Stromberg and Gabor T. Marth: BamTools: a C++ API and toolkit for analyzing and managing BAM files. (PubMed,eprint) Bioinformatics 27(12):1691-2 (2011)
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Bandage
Bioinformatics Application for Navigating De novo Assembly Graphs Easily
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Bandage is a GUI program that allows users to interact with the assembly graphs made by de novo assemblers such as Velvet, SPAdes, MEGAHIT and others.

De novo assembly graphs contain not only assembled contigs but also the connections between those contigs, which were previously not easily accessible. Bandage visualises assembly graphs, with connections, using graph layout algorithms. Nodes in the drawn graph, which represent contigs, can be automatically labelled with their ID, length or depth. Users can interact with the graph by moving, labelling and colouring nodes. Sequence information can also be extracted directly from the graph viewer. By displaying connections between contigs, Bandage opens up new possibilities for analysing and improving de novo assemblies that are not possible by looking at contigs alone.

More information and download links are on the Bandage website: rrwick.github.io/Bandage

The package is relevant to the field of genome assembly and will be maintained by the Debian Med team.

Please cite: Ryan R. Wick, Mark B. Schultz, Justin Zobel and Kathryn E. Holt: Bandage: interactive visualisation of de novo genome assemblies. (PubMed,eprint) Bioinformatics 31(20):3350-3352 (2015)
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Barrnap
rapid ribosomal RNA prediction
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Barrnap (BAsic Rapid Ribosomal RNA Predictor) predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).

It takes FASTA DNA sequence as input, and writes GFF3 as output. It uses the NHMMER tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.

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Bcftools
genomic variant calling and manipulation of VCF/BCF files
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BCFtools is a set of utilities that manipulate variant calls in the Variant Call Format (VCF) and its binary counterpart BCF. All commands work transparently with both VCFs and BCFs, both uncompressed and BGZF-compressed.

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Beads
2-DE electrophoresis gel image spot detection
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BEADS is a program for spot detection on 2-D gel images. It is based on an analogy with beads flowing uphill on the surface of the gel image and on the analysis of their paths (Langella & Zivy, 2008).

Please cite: Olivier Langella and Michel Zivy: A method based on bead flows for spot detection on 2-D gel images. (PubMed) Proteomics 8(23-24):4914-8 (2008)
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Beagle
Genotype calling, genotype phasing and imputation of ungenotyped markers
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Beagle performs genotype calling, genotype phasing, imputation of ungenotyped markers, and identity-by-descent segment detection. Genotypic imputation works on phased haplotypes using a Li and Stephens haplotype frequency model. Beagle also implements the Refined IBD algorithm for detecting homozygosity-by-descent (HBD) and identity-by-descent (IBD) segments.

The package is enhanced by the following packages: beagle-doc
Please cite: Sharon R. Browning and Brian L. Browning: Rapid and Accurate Haplotype Phasing and Missing-Data Inference for Whole-Genome Association Studies By Use of Localized Haplotype Clustering. (eprint) The American Journal of Human Genetics 81(5):1084-1097 (2007)
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Beast-mcmc
Bayesian MCMC phylogenetic inference
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BEAST is a cross-platform program for Bayesian MCMC analysis of molecular sequences. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. Included is a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.

The package is enhanced by the following packages: beast-mcmc-doc beast-mcmc-examples
Please cite: Alexei J Drummond and Andrew Rambaut: BEAST: Bayesian evolutionary analysis by sampling trees. (PubMed,eprint) BMC Evol Biol 8(7):214 (2007)
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Beast2-mcmc
Bayesian MCMC phylogenetic inference
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BEAST is a cross-platform program for Bayesian MCMC analysis of molecular sequences. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. Included is a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.

This is no new upstream version of beast-mcmc (1.x) but rather a rewritten version.

The package is enhanced by the following packages: beast2-mcmc-doc beast2-mcmc-examples
Please cite: Remco Bouckaert, Joseph Heled, Denise Kühnert, Tim Vaughan, Chieh-Hsi Wu, Dong Xie, Marc A. Suchard, Andrew Rambaut and Alexei J. Drummond: BEAST 2: A Software Platform for Bayesian Evolutionary Analysis. (PubMed,eprint) PLoS Comput Biol 10(4):e1003537 (2014)
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Bedops
high-performance genomic feature operations
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BEDOPS is a suite of tools to address common questions raised in genomic studies, mostly with regard to overlap and proximity relationships between data sets. It aims to be scalable and flexible, facilitating the efficient and accurate analysis and management of large-scale genomic data.

Please cite: Shane Neph, M. Scott Kuehn, Alex P. Reynolds, Eric Haugen, Robert E. Thurman, Audra K. Johnson, Eric Rynes, Matthew T. Maurano, Jeff Vierstra, Sean Thomas, Richard Sandstrom, Richard Humbert and John A. Stamatoyannopoulos: BEDOPS: high-performance genomic feature operations. (PubMed,eprint) 28(14):1919-1920 (2012)
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Bedtools
suite of utilities for comparing genomic features
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The BEDTools utilities allow one to address common genomics tasks such as finding feature overlaps and computing coverage. The utilities are largely based on four widely-used file formats: BED, GFF/GTF, VCF, and SAM/BAM. Using BEDTools, one can develop sophisticated pipelines that answer complicated research questions by streaming several BEDTools together.

The groupBy utility is distributed in the filo package.

Please cite: Aaron R. Quinlan and Ira M. Hall: BEDTools: a flexible suite of utilities for comparing genomic features. (PubMed,eprint) Bioinformatics 26(6):841-842 (2010)
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Belvu
multiple sequence alignment viewer and phylogenetic tool
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Belvu is a multiple sequence alignment viewer and phylogenetic tool with an extensive set of user-configurable modes to color residues.

  • View multiple sequence alignments.
  • Residues can be coloured by conservation, with user-configurable cutoffs and colours.
  • Residues can be coloured by residue type (user-configurable).
  • Colour schemes can be imported or exported.
  • Swissprot (or PIR) entries can be fetched by double clicking.
  • The position in the alignment can be easily tracked.
  • Manual deletion of rows and columns.
  • Automatic editing of rows and columns based on customisable criteria:
    • removal of all-gap columns;
    • removal of all gaps;
    • removal of redundant sequences;
    • removal of a column by a user-specified percentage of gaps;
    • filtering of sequences by percent identity;
    • removal of sequences by a user-specified percentage of gaps;
    • removal of partial sequences (those starting or ending with gaps); and
    • removal of columns by conservation (with user-specified upper/lower cutoffs).
  • The alignment can be saved in Stockholm, Selex, MSF or FASTA format.
  • Distance matrices between sequences can be generated using a variety of distance metrics.
  • Distance matrices can be imported or exported.
  • Phylogenetic trees can be constructed based on various distance-based tree reconstruction algorithms.
  • Trees can be saved in New Hampshire format.
  • Belvu can perform bootstrap phylogenetic reconstruction.
Please cite: Gemma Barson and Ed Griffiths: SeqTools: visual tools for manual analysis of sequence alignments. (PubMed,eprint) BMC Research Notes 9:39 (2016)
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Berkeley-express
Streaming quantification for high-throughput sequencing
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eXpress is a streaming tool for quantifying the abundances of a set of target sequences from sampled subsequences. Example applications include transcript-level RNA-Seq quantification, allele-specific/haplotype expression analysis (from RNA-Seq), transcription factor binding quantification in ChIP-Seq, and analysis of metagenomic data. It is based on an online-EM algorithm that results in space (memory) requirements proportional to the total size of the target sequences and time requirements that are proportional to the number of sampled fragments. Thus, in applications such as RNA-Seq, eXpress can accurately quantify much larger samples than other currently available tools greatly reducing computing infrastructure requirements. eXpress can be used to build lightweight high-throughput sequencing processing pipelines when coupled with a streaming aligner (such as Bowtie), as output can be piped directly into eXpress, effectively eliminating the need to store read alignments in memory or on disk.

In an analysis of the performance of eXpress for RNA-Seq data, it was observed that this efficiency does not come at a cost of accuracy. eXpress is more accurate than other available tools, even when limited to smaller datasets that do not require such efficiency. Moreover, like the Cufflinks program, eXpress can be used to estimate transcript abundances in multi-isoform genes. eXpress is also able to resolve multi-mappings of reads across gene families, and does not require a reference genome so that it can be used in conjunction with de novo assemblers such as Trinity, Oases, or Trans-ABySS. The underlying model is based on previously described probabilistic models developed for RNA-Seq but is applicable to other settings where target sequences are sampled, and includes parameters for fragment length distributions, errors in reads, and sequence-specific fragment bias.

eXpress can be used to resolve ambiguous mappings in other high-throughput sequencing based applications. The only required inputs to eXpress are a set of target sequences and a set of sequenced fragments multiply-aligned to them. While these target sequences will often be gene isoforms, they need not be. Haplotypes can be used as the reference for allele-specific expression analysis, binding regions for ChIP-Seq, or target genomes in metagenomics experiments. eXpress is useful in any analysis where reads multi-map to sequences that differ in abundance.

Please cite: Adam Roberts and Lior Pachter: Streaming fragment assignment for real-time analysis of sequencing experiments. (PubMed) Nature Methods 10(1):71–73 (2013)
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Bio-eagle
Haplotype phasing within a genotyped cohort or using a phased reference panel
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Eagle estimates haplotype phase either within a genotyped cohort or using a phased reference panel. The basic idea of the Eagle1 algorithm is to harness identity-by-descent among distant relatives—which is pervasive at very large sample sizes but rare among smaller numbers of samples—to rapidly call phase using a fast scoring approach. In contrast, the Eagle2 algorithm analyzes a full probabilistic model similar to the diploid Li-Stephens model used by previous HMM-based methods.

Please note: The executable was renamed to bio-eagle because of a name clash. Please read more about this in /usr/share/doc/bio-eagle/README.Debian.

The package is enhanced by the following packages: bio-eagle-examples
Please cite: Po-Ru Loh, Pier Francesco Palamara and Alkes L Price: Fast and accurate long-range phasing in a UK Biobank cohort. Nature Genetics (2016)
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Bio-rainbow
clustering and assembling short reads for bioinformatics
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Efficient tool for clustering and assembling short reads, especially for RAD.

Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top-down manner. long a guided tree, it iteratively merges sibling leaves in a bottom-up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, it is shown that Rainbow is more competent than the other tools in dealing with RAD-seq data.

Please cite: Zechen Chong, Jue Ruan and Chung-I. Wu: Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads.. (PubMed) Bioinformatics 28(21):2732-2737 (2012)
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Bio-tradis
analyse the output from TraDIS analyses of genomic sequences
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Bio-Tradis contains a set of tools to analyse the output from TraDIS analyses.

The Bio-Tradis analysis pipeline is implemented as an extensible Perl library which can either be used as is, or as a basis for the development of more advanced analysis tools.

Please note: You need to manually install BioConductor Edger which can not be distributed by Debian in recent version since it is using non-distributable code locfit.

Please cite: Lars Barquist, Matthew Mayho, Carla Cummins, Amy K. Cain, Christine J. Boinett, Andrew J. Page, Gemma C. Langridge, Michael A. Quail, Jacqueline A. Keane and Julian Parkhill: The TraDIS toolkit: sequencing and analysis for dense transposon mutant libraries. (PubMed,eprint) Bioinformatics 32(7):1109-1111 (2016)
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Biosyntax-gedit
Syntax Highlighting for Computational Biology (gedit)
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Syntax highlighting for computational biology to bring you intuitively close to your data. BioSyntax supports .sam, .flagstat, .vcf, .fasta, .fastq, .faidx , .clustal, .pdb, .gtf, .bed files & more.

This package provides the bioSyntax plugin for gedit.

Please note: The plugin is not enabled per default, to enable it, please read: /usr/share/doc/biosyntax-gedit/README.Debian

Please cite: Artem Babaian, Anicet Ebou, Alyssa Fegen, Ho Yin Jeffrey Kam, German E Novakovsky, Jasper Wong, Dylan Aïssi and Li Yao: bioSyntax: syntax highlighting for computational biology. BMC Bioinformatics 19(303) (2018)
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Screenshots of package biosyntax-gedit
Remark of Debian Med team: Plugins for vim (biosyntax-vim) and less (biosyntax-less) are also available.
Bitseq
Bayesian Inference of Transcripts from Sequencing Data
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BitSeq is an application for inferring expression levels of individual transcripts from sequencing (RNA-Seq) data and estimating differential expression (DE) between conditions. An advantage of this approach is the ability to account for both technical uncertainty and intrinsic biological variance in order to avoid false DE calls. The technical contribution to the uncertainty comes both from finite read-depth and the possibly ambiguous mapping of reads to multiple transcripts.

Please cite: James Hensman, Panagiotis Papastamoulis, Peter Glaus, Antti Honkela and Magnus Rattray: Fast and accurate approximate inference of transcript expression from RNA-seq data. (PubMed,eprint) Bioinformatics 31(24):3881-9 (2015)
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Blasr
mapping single-molecule sequencing reads
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Basic local alignment with successive refinement (BLASR) is a method for mapping single-molecule sequencing reads against a reference genome. Such reads are thousands of bases long, with divergence between them and the genome being dominated by insertion and deletion error.

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Blixem
interactive browser of sequence alignments
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Blixem is an interactive browser of sequence alignments that have been stacked up in a "master-slave" multiple alignment; it is not a 'true' multiple alignment but a 'one-to-many' alignment.

  • Overview section showing the positions of genes and alignments around the alignment window
  • Detail section showing the actual alignment of protein or nucleotide sequences to the genomic DNA sequence.
  • View alignments against both strands of the reference sequence.
  • View sequences in nucleotide or protein mode; in protein mode, Blixem will display the three-frame translation of the reference sequence.
  • Residues are highlighted in different colours depending on whether they are an exact match, conserved substitution or mismatch.
  • Gapped alignments are supported, with insertions and deletions being highlighted in the match sequence.
  • Matches can be sorted and filtered.
  • SNPs and other variations can be highlighted in the reference sequence.
  • Poly(A) tails can be displayed and poly(A) signals highlighted in the reference sequence.
Please cite: Gemma Barson and Ed Griffiths: SeqTools: visual tools for manual analysis of sequence alignments. (PubMed,eprint) BMC Research Notes 9:39 (2016)
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Bolt-lmm
Efficient large cohorts genome-wide Bayesian mixed-model association testing
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The BOLT-LMM software package currently consists of two main algorithms, the BOLT-LMM algorithm for mixed model association testing, and the BOLT-REML algorithm for variance components analysis (i.e., partitioning of SNP-heritability and estimation of genetic correlations).

The BOLT-LMM algorithm computes statistics for testing association between phenotype and genotypes using a linear mixed model. By default, BOLT-LMM assumes a Bayesian mixture-of-normals prior for the random effect attributed to SNPs other than the one being tested. This model generalizes the standard infinitesimal mixed model used by previous mixed model association methods, providing an opportunity for increased power to detect associations while controlling false positives. Additionally, BOLT-LMM applies algorithmic advances to compute mixed model association statistics much faster than eigendecomposition-based methods, both when using the Bayesian mixture model and when specialized to standard mixed model association.

The BOLT-REML algorithm estimates heritability explained by genotyped SNPs and genetic correlations among multiple traits measured on the same set of individuals. BOLT-REML applies variance components analysis to perform these tasks, supporting both multi-component modeling to partition SNP-heritability and multi-trait modeling to estimate correlations. BOLT-REML applies a Monte Carlo algorithm that is much faster than eigendecomposition-based methods for variance components analysis at large sample sizes.

The package is enhanced by the following packages: bolt-lmm-example
Please cite: Po-Ru Loh, George Tucker, Brendan K Bulik-Sullivan, Bjarni J Vilhjálmsson, Hilary K Finucane, Rany M Salem, Daniel I Chasman, Paul M Ridker, Benjamin M Neale, Bonnie Berger, Nick Patterson and Alkes L Price: Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nature Genetics (2015)
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Bowtie
Ultraschnelles und speichersparendes Alignmentprogramm für kurze DNA-Sequenzen
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Dieses Paket beschäftigt sich mit dem Problem die Resultate der neuesten (2010) DNA-Sequenziertechniken zu interpretieren. Diese Techniken ergeben ziemlich kurze Sequenzen, die nicht direkt interpretiert werden können. Es ist die Aufgabe für Werkzeuge wie Bowtie den chromosomalen Ort (Locus) der kurzen DNA-Sequenzen festzustellen.

Bowtie führt Alignments kurzer DNA-Sequenzen (Reads) mit dem menschlichen Genom durch, mit einer Rate von über 25 Millionen Reads (mit einer Länge von 35 Basenpaaren) pro Stunde. Bowtie indiziert das Genom mit einer Burrows-Wheeler-Transformation, um den Speicherverbrauch gering zu halten; normalerweise etwa 2,2 GB für das menschliche Genom (2,9 GB für »paired- end«).

The package is enhanced by the following packages: bowtie-examples
Please cite: Ben Langmead, Cole Trapnell, Mihai Pop and Steven L Salzberg: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. (eprint) Genome Biology 10:R25 (2009)
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Bowtie2
Ultraschnelles und speichersparendes Alignmentprogramm für kurze DNA-Sequenzen
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Bowtie 2 ist ein ultraschnelles und speichersparendes Werkzeug für Alignment zwischen kurzen DNA-Sequenzen (Reads) zu langen Referenzsequenzen. Es ist besonders gut beim Ausrichten von Reads von etwa 50 bis Hunderte oder Tausende Zeichen und besonders gut beim Ausrichten an relativ großen Genomen (z.B. von Säugetieren).

Bowtie 2 indiziert das Genom mit einem FM-Index, um den Speicherbedarf gering zu halten; für das menschliche Genom beträgt der Speicherbedarf etwa 3,2 GB. Bowtie 2 unterstützt Modi für Gaps sowie lokale und »Paired-End«-Alignments.

The package is enhanced by the following packages: bowtie2-examples
Please cite: Ben Langmead and Steven L Salzberg: Fast gapped-read alignment with Bowtie 2. (PubMed) Nature Methods 9:357–359 (2012)
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Boxshade
Pretty-printing von multiplen Sequenzalignments
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Boxshade erstellt gut aussehende Darstellungen von Alignments von Protein- oder DNA-Sequenzen. Das Programm alignt die Sequenzen nicht selbst, sondern benötigt als Eingabe eine Datei, die automatisch von einem Programm für Multiple Alignments oder manuell mit einem Alignment-Editor erstellt wurde.

Boxshade liest Alignments in den Formaten PILEUP-MSF, CLUSTAL-ALN, MALIGNED-data und ESEE-save (bis zu 150 Sequenzen von maximal je 10000 Elementen). Verschiedene Regeln für die Schattierung und Färbung werden angeboten, um biochemische Ähnlichkeiten der Seitenketten in den Spalten zu reflektieren. Die Ausgabe erfolgt auf den Bildschirm oder in eine Datei. Angeboten werden die Formate ANSI/VT100, PS/EPS, RTF, HPGL, ReGIS, LJ250-printer, ASCII, xFIG, PICT und HTML.

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Bppphyview
Bio++ Phylogenetic Viewer
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A phylogenetic tree editor developed using Bio++ and Qt. Phyview allows one to visualize, edit, print and output phylogenetic trees and associated data.

Bppsuite
Bio++ program suite
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The Bio++ Program Suite is a package of programs using the Bio++ libraries and dedicated to Phylogenetics and Molecular Evolution. All programs are independent, but can be combined to perform rather complex analyses. These programs use the interface helper tools of the libraries, and hence share the same syntax. They also have several options in common, which may also be shared by third-party software.

The following programs are included:

  • BppML for maximum likelihood analysis,
  • BppSeqGen for sequences simulation,
  • BppAncestor for ancestral states reconstruction,
  • BppDist for distance methods,
  • BppPars for parsimony analysis,
  • BppSeqMan for file conversion and sequence manipulation,
  • BppConsense for building consensus tree and computing bootstrap values,
  • BppReRoot for tree rerooting.
  • BppTreeDraw for tree drawing.
  • BppAlnScore for comparing alignments and computing alignment scores.
  • BppMixedLikelihoods for computing site per site likelihoods of components of mixture models.
  • BppPopGen for population genetics analyses.
The package is enhanced by the following packages: bppsuite-examples
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Brig
BLAST Ring Image Generator
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BRIG can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data.

  • Images show similarity between a central reference sequence and other sequences as concentric rings.
  • BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.
  • Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.
  • Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.
  • BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously
Please cite: Nabil-Fareed Alikhan, Nicola K Petty, Nouri L Ben Zakour and Scott A Beatson: BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. (PubMed,eprint) BMC Genomics 12:402 (2011)
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Bwa
Burrows-Wheeler Aligner
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BWA (Burrows-Wheeler Aligner) ist ein Softwarepaket für das Abbilden gering abweichender Sequenzen auf eine große Referenzsequenz, etwa das menschliche Genom. Es besteht aus drei Algorithmen: BWA-backtrack, BWA-SW und BWA-MEM. BWA-backtrack ist für Illumina-Sequenz-Reads bis zu 100 Basenpaaren (bp) geeignet, während die anderen zwei Algorithmen für längere Sequenzen zwischen 70 bp und 1 Megabasenpaaren (Mbp) geeignet sind. BWA-MEM und BWA-SW teilen ähnliche Merkmale wie Unterstützung für lange Reads und Split-Alignments. BWA-MEM ist jedoch neuer und wird für hochqualitative Anfragen empfohlen, da es schneller und genauer ist. BWA-MEM ist zudem für Illumina-Reads mit einer Länge von 70 bis 100 bp leistungsfähiger als BWA-backtrack.

Please cite: Heng Li and Richard Durbin: Fast and accurate short read alignment with Burrows-Wheeler transform. (PubMed,eprint) Bioinformatics 25(14):1754-1760 (2009)
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Canu
single molecule sequence assembler for genomes
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Canu is a fork of the Celera Assembler, designed for high-noise single-molecule sequencing (such as the PacBio RS II or Oxford Nanopore MinION).

Canu is a hierarchical assembly pipeline which runs in four steps:

  • Detect overlaps in high-noise sequences using MHAP
  • Generate corrected sequence consensus
  • Trim corrected sequences
  • Assemble trimmed corrected sequences
Please cite: Sergey Koren, Brian P. Walenz, Konstantin Berlin, Jason R. Miller and Adam M. Phillippy: Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. bioRxiv (2016)
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Remark of Debian Med team: Genome assembly and large-scale genome alignment (http://www.cbcb.umd.edu/software/)
Cassiopee
index and search tool in genomic sequences
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Cassiopee index and search library C implementation. It is a complete rewrite of the ruby Cassiopee gem. It scans an input genomic sequence (dna/rna/protein) and search for a subsequence with exact match or allowing substitutions (Hamming distance) and/or insertion/deletions.

This package contains the cassiopee and cassiopeeknife tools.

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Cct
visually comparing bacterial, plasmid, chloroplast, or mitochondrial sequences
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The CGView Comparison Tool (CCT) is a package for visually comparing bacterial, plasmid, chloroplast, or mitochondrial sequences of interest to existing genomes or sequence collections. The comparisons are conducted using BLAST, and the BLAST results are presented in the form of graphical maps that can also show sequence features, gene and protein names, COG category assignments, and sequence composition characteristics. CCT can generate maps in a variety of sizes, including 400 Megapixel maps suitable for posters. Comparisons can be conducted within a particular species or genus, or all available genomes can be used. The entire map creation process, from downloading sequences to redrawing zoomed maps, can be completed easily using scripts included with the CCT. User-defined features or analysis results can be included on maps, and maps can be extensively customized. To simplify program setup, a CCT virtual machine that includes all dependencies preinstalled is available. Detailed tutorials illustrating the use of CCT are included with the CCT documentation.

Please cite: Jason R Grant, Adriano S Arantes and Paul Stothard: Comparing thousands of circular genomes using the CGView Comparison Tool. (PubMed,eprint) BMC Genomics 13:202 (2012)
Cd-hit
Programme zur schnellen Gruppierung von Sequenzen
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cd-hit enthält eine Anzahl an Programmen, um Sequenzen zu gruppieren. cd-hit gruppiert Proteine zu Clustern, die eine benutzerdefinierte Ähnlichkeitsschwelle einhalten. cd-hit-est ähnelt cd-hit, gruppiert allerdings Nukleotidsequenzen (ohne Introns). cd-hit-est2 ähnelt cd-hit-est, vergleicht jedoch zwei Nukleotid-Datensätze. Eine Anzahl an weiteren zugehörigen Programmen sind ebenfalls in diesem Paket enthalten. Weitere Informationen finden Sie im Benutzerhandbuch von cd-hit, das auch Teil dieses Pakets ist.

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Cdbfasta
CDB-Werkzeuge zur Indizierung und Abfrage für multi-FASTA-Dateien
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CDB (Constant DataBase) kann zur Index-Erstellung verwendet werden, damit jede bestimmte Sequenz in großen multi-FASTA-Dateien schnell gefunden werden kann. Um Platz zu sparen, besitzt es die Option Dateneinträge zu komprimieren.

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Centrifuge
rapid and memory-efficient system for classification of DNA sequences
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Centrifuge is a very rapid and memory-efficient system for the classification of DNA sequences from microbial samples, with better sensitivity than and comparable accuracy to other leading systems. The system uses a novel indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index, optimized specifically for the metagenomic classification problem. Centrifuge requires a relatively small index (e.g., 4.3 GB for ~4,100 bacterial genomes) yet provides very fast classification speed, allowing it to process a typical DNA sequencing run within an hour. Together these advances enable timely and accurate analysis of large metagenomics data sets on conventional desktop computers.

Please cite: Daehwan Kim, Li Song, Florian P. Breitwieser and Steven L. Salzberg: Centrifuge: rapid and sensitive classification of metagenomic sequences. (PubMed,eprint) Genome Research 26(12):1721-1729 (2016)
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Cgview
Circular Genome Viewer
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CGView is a Java package for generating high quality, zoomable maps of circular genomes. Its primary purpose is to serve as a component of sequence annotation pipelines, as a means of generating visual output suitable for the web. Feature information and rendering options are supplied to the program using an XML file, a tab delimited file, or an NCBI ptt file. CGView converts the input into a graphical map (PNG, JPG, or Scalable Vector Graphics format), complete with labels, a title, legends, and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any web browser, allowing rapid genome browsing, and facilitating data sharing. The feature labels in maps can be hyperlinked to external resources, allowing CGView maps to be integrated with existing web site content or databases.

In addition to the CGView application, an API is available for generating maps from within other Java applications, using the cgview package.

CGView can be used for any of the following:

  • Bacterial genome visualization and browsing - CGView can be incorporated into bacterial genome annotation pipelines, as a means of generating web content for data visualization and navigation. The PNG and image map content does not require Java applets or special browser plugins.
  • Genome poster generation - CGView can generate poster-sized images of circular genomes in rasterized image formats or in Scalable Vector Graphics format.
  • Sequence analysis visualization - CGView can be used to display the output of sequence analysis programs in a circular context.

CGView features:

  • Images can be generated in PNG, JPG, or SVG format. See the CGView gallery.
  • Static or interactive maps can be generated. The interactive maps make use of standard PNG images and HTML image maps. Scalable Vector Graphics output is included in the interactive maps (see example).
  • The XML input allows complete control over the appearance of the map.
  • Tab delimited input files and NCBI ptt files can be used as an alternative to the XML format.
  • The CGView API can be used to incorporate CGView into Java applications.
  • The CGView applet can be used to incorporate zoomable maps into web pages (see example).
  • The CGView Server can be used to generate maps online.
Please cite: Paul Stothard and David S. Wishart: Circular genome visualization and exploration using CGView. (PubMed,eprint) Bioinformatics 21(4):537-539 (2004)
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Changeo
Repertoire clonal assignment toolkit (Python 3)
Maintainer: Steffen Moeller
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Change-O is a collection of tools for processing the output of V(D)J alignment tools, assigning clonal clusters to immunoglobulin (Ig) sequences, and reconstructing germline sequences.

Dramatic improvements in high-throughput sequencing technologies now enable large-scale characterization of Ig repertoires, defined as the collection of trans-membrane antigen-receptor proteins located on the surface of B cells and T cells. Change-O is a suite of utilities to facilitate advanced analysis of Ig and TCR sequences following germline segment assignment. Change-O handles output from IMGT/HighV-QUEST and IgBLAST, and provides a wide variety of clustering methods for assigning clonal groups to Ig sequences. Record sorting, grouping, and various database manipulation operations are also included.

This package installs the library for Python 3.

Please cite: Namita T. Gupta, Jason A. Vander Heiden, Mohamed Uduman, Daniel Gadala-Maria, Gur Yaari and Steven H. Kleinstein: Link to publication (PubMed,eprint) Bioinformatics 31(20):3356-3358 (2015)
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Chimeraslayer
detects likely chimeras in PCR amplified DNA
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ChimeraSlayer is a chimeric sequence detection utility, compatible with near-full length Sanger sequences and shorter 454-FLX sequences (~500bp).

Chimera Slayer involves the following series of steps that operate to flag chimeric 16S rRNA sequences:

 1. the ends of a query sequence are searched against an included
    database of reference chimera-free 16S sequences to identify potential
    parents of a chimera
 2. candidate parents of a chimera are selected as those that form a
    branched best scoring alignment to the NAST-formatted query sequence
 3. the NAST alignment of the query sequence is improved in a
    ‘chimera-aware’ profile-based NAST realignment to the selected
    reference parent sequences
 4. an evolutionary framework is used to flag query sequences found to
    exhibit greater sequence homology to an in silico chimera formed
    between any two of the selected reference parent sequences.

To run Chimera Slayer, you need NAST-formatted sequences generated by the nast-ier utility.

ChimeraSlayer is part of the microbiomeutil suite.

The package is enhanced by the following packages: microbiomeutil-data
Please cite: Brian J. Haas, Dirk Gevers, Ashlee M. Earl, Mike Feldgarden, Doyle V. Ward, Georgia Giannoukos, Dawn Ciulla, Diana Tabbaa, Sarah K. Highlander, Erica Sodergren, Barbara Methé, Todd Z. DeSantis, The Human Microbiome Consortium, Joseph F. Petrosino, Rob Knight and Bruce W. Birren: Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. (PubMed,eprint) Genome Research 21(3):494-504 (2011)
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Chromhmm
Chromatin state discovery and characterization
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ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks. ChromHMM is based on a multivariate Hidden Markov Model that explicitly models the presence or absence of each chromatin mark. The resulting model can then be used to systematically annotate a genome in one or more cell types. By automatically computing state enrichments for large-scale functional and annotation datasets ChromHMM facilitates the biological characterization of each state. ChromHMM also produces files with genome-wide maps of chromatin state annotations that can be directly visualized in a genome browser.

The package is enhanced by the following packages: chromhmm-example
Please cite: Jason Ernst and Manolis Kellis: ChromHMM: automating chromatin-state discovery and characterization. (eprint) Nature Methods 9(3):215-216 (2012)
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Chromimpute
Large-scale systematic epigenome imputation
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ChromImpute takes an existing compendium of epigenomic data and uses it to predict signal tracks for mark-sample combinations not experimentally mapped or to generate a potentially more robust version of data sets that have been mapped experimentally. ChromImpute bases its predictions on features from signal tracks of other marks that have been mapped in the target sample and the target mark in other samples with these features combined using an ensemble of regression trees.

Please cite: Jason Ernst and Manolis Kellis: Large-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues. (eprint) Nature Biotechnology 33(4):364-376 (2015)
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Circlator
circularize genome assemblies
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Circlator is a tool to automate assembly circularization for bacterial and small eukaryotic genomes and produce accurate linear representations of circular sequences.

Please cite: Martin Hunt, Nishadi De Silva, Thomas D. Otto, Julian Parkhill, Jacqueline A. Keane and Simon R. Harris: Circlator: automated circularization of genome assemblies using long sequencing reads. (PubMed) Genome Biology 29(16):294 (2015)
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Circos
plotter for visualizing data
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Circos visualizes data in a circular layout — ideal for exploring relationships between objects or positions, and creating highly informative publication-quality graphics.

This package provides the Circos plotting engine, which is command-line driven (like gnuplot) and fully scriptable.

Please cite: Martin I Krzywinski, Jacqueline E Schein, Inanc Birol, Joseph Connors, Randy Gascoyne, Doug Horsman, Steven J Jones and Marco A Marra: Circos: An information aesthetic for comparative genomics. (PubMed,eprint) Genome Research 19(9):1639-45 (2009)
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Clearcut
extremely efficient phylogenetic tree reconstruction
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Clearcut is the reference implementation for the Relaxed Neighbor Joining (RNJ) algorithm by J. Evans, L. Sheneman, and J. Foster from the Initiative for Bioinformatics and Evolutionary Studies (IBEST) at the University of Idaho.

Please cite: Jason Evans, Luke Sheneman and James A. Foster: Relaxed Neighbor-Joining: A Fast Distance-Based Phylogenetic Tree Construction Method. (PubMed) J. Mol. Evol. 62(6):785-792 (2006)
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Clonalframe
inference of bacterial microevolution using multilocus sequence data
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ClonalFrame identifies the clonal relationships between the members of a sample, while also estimating the chromosomal position of homologous recombination events that have disrupted the clonal inheritance.

ClonalFrame can be applied to any kind of sequence data, from a single fragment of DNA to whole genomes. It is well suited for the analysis of MLST data, where 7 gene fragments have been sequenced, but becomes progressively more powerful as the sequenced regions increase in length and number up to whole genomes. However, it requires the sequences to be aligned. If you have genomic data that is not aligned, it is recommend to use Mauve which produces alignment of whole bacterial genomes in exactly the format required for analysis with ClonalFrame.

Please cite: Xavier Didelot and Daniel Falush: Inference of Bacterial Microevolution Using Multilocus Sequence Data. (PubMed,eprint) Genetics Advance 175:1251-1266 (2006)
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Clonalframeml
Efficient Inference of Recombination in Whole Bacterial Genomes
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ClonalFrameML is a software package that performs efficient inference of recombination in bacterial genomes. ClonalFrameML was created by Xavier Didelot and Daniel Wilson. ClonalFrameML can be applied to any type of aligned sequence data, but is especially aimed at analysis of whole genome sequences. It is able to compare hundreds of whole genomes in a matter of hours on a standard Desktop computer. There are three main outputs from a run of ClonalFrameML: a phylogeny with branch lengths corrected to account for recombination, an estimation of the key parameters of the recombination process, and a genomic map of where recombination took place for each branch of the phylogeny.

ClonalFrameML is a maximum likelihood implementation of the Bayesian software ClonalFrame which was previously described by Didelot and Falush (2007). The recombination model underpinning ClonalFrameML is exactly the same as for ClonalFrame, but this new implementation is a lot faster, is able to deal with much larger genomic dataset, and does not suffer from MCMC convergence issues

Please cite: Xavier Didelot and Daniel J. Wilson: ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes. (PubMed,eprint) PLoS Comput Biology 11(2):e1004041 (2015)
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Clonalorigin
inference of homologous recombination in bacteria using whole genome sequences
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Bacteria, unlike us, can reproduce on their own. They do however have mechanisms that transfer DNA between organisms, a process more formally known as recombination. The mechanisms by which recombination takes place have been studied extensively in the laboratory but much remains to be understood concerning how, when and where recombination takes place within natural populations of bacteria and how it helps them to adapt to new environments. ClonalOrigin performs a comparative analysis of the sequences of a sample of bacterial genomes in order to reconstruct the recombination events that have taken place in their ancestry.

Please cite: Xavier Didelot, Daniel Lawson, Aaron Darling and Daniel Falush: Inference of Homologous Recombination in Bacteria Using Whole-Genome Sequences. (PubMed,eprint) Genetics 186(4):1435-1449 (2010)
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Clustalo
Universalprogramm für multiple Sequenzalignments (MSA) von Proteinen
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Clustal-Omega ist ein Universalprogramm für multiple Sequenzalignments (MSA) von DNA/RNA/Proteinen. Es erstellt qualitativ hochwertige MSAs und kann Datensätze bestehend aus hunderttausenden von Sequenzen in angemessener Zeit verarbeiten.

Please cite: Fabian Sievers, Andreas Wilm, David Dineen, Toby J Gibson, Kevin Karplus, Weizhong Li, Rodrigo Lopez, Hamish McWilliam, Michael Remmert, Johannes Söding, Julie D Thompson and Desmond G Higgins: Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. (PubMed) Molecular Systems Biology 7(539) (2011)
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Clustalw
Globale multiple Alignments von Nukleotid- oder Peptidsequenzen
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Clustal W führt ein Alignment mehrerer Nukleotid- oder Aminosäurensequenzen aus. Das Programm erkennt das Format der Eingabesequenzen und ob die Sequenzen aus Nuklein- (DNA/RNA) oder Aminosäuren (Proteine) bestehen. Das Ausgabeformat kann aus verschiedenen Formaten für multiple Alignments ausgewählt werden, etwa Phylip oder FASTA. Clustal W ist allgemein anerkannt.

Die Ausgabe von Clustal W kann händisch editiert werden, jedoch wird ein Alignment-Editor wie SeaView oder Clustal X empfohlen. Bei der Erstellung eines Modells aus Ihrem Alignment, kann die Ausgabe für verbesserte Datenbanksuchen verwendet werden. Das Debian-Paket hmmer erstellt dies mittels eines Hidden-Markov-Modells (HMM).

The package is enhanced by the following packages: clustalw-mpi
Please cite: M. A. Larkin, G. Blackshields, N. P. Brown, R. Chenna, P. A. McGettigan, H. McWilliam, F. Valentin, I.M. Wallace, A. Wilm, R. Lopez, J. D. Thompson, T. J. Gibson and D. G. Higgins: Clustal W and Clustal X version 2.0. (PubMed,eprint) Bioinformatics 23(21):2947-2948 (2007)
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Clustalx
Multiples Alignment von Nukleotid- und Proteinsequenzen (grafische Oberfläche)
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Dieses Paket enthält eine grafische Oberfläche für Clustal, ein Programm für multiple Sequenzalignments. Das Paket enthält für die Analyse der Resultate eine integrierte Umgebung für multiple Sequenz- und Profilalignments. Das Sequenzalignment wird in einem Fenster angezeigt. Es wurde ein vielseitiges Farbschema implementiert, um konservierte Teile des Alignments hervorzuheben. Für professionelle Präsentationen ist das LaTeX-Paket texshade oder boxshade besser geeignet.

Sie können alle Optionen für herkömmliche multiple Sequenz- und Profilaligments über Pull-Down-Menüs am oberen Rand des Fensters erreichen. Sie können Sequenzen ausschneiden und einfügen, um die Alignment-Reihenfole zu ändern; Sie können eine Untermenge an Sequenzen auswählen, die verglichen werden sollen; Sie können einen Teilbereich des Alignments auswählen, neu anordnen und wieder in das ursprüngliche Alignment einfügen.

Es kann eine Qualitätsanlayse des Alignments durchgeführt werden. Außerdem können Segmente mit geringem Score oder ungewöhnlichen Resten hervorgehoben werden.

Please cite: M.A. Larkin, G. Blackshields, N.P. Brown, R. Chenna, P.A. McGettigan, H. McWilliam, F. Valentin, I.M. Wallace, A. Wilm, R. Lopez, J.D. Thompson, T.J. Gibson and D.G. Higgins: Clustal W and Clustal X version 2.0. (PubMed,eprint) Bioinformatics 23(21):2947-2948 (2007)
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Cnvkit
Copy number variant detection from targeted DNA sequencing
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A command-line toolkit and Python library for detecting copy number variants and alterations genome-wide from targeted DNA sequencing. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Please cite: Eric Talevich, A. Hunter Shain, Thomas Botton and Boris C. Bastian: CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing. (PubMed,eprint) PLOS 12(4):e1004873 (2016)
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Codonw
Correspondence Analysis of Codon Usage
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CodonW is a package for codon usage analysis. It was designed to simplify Multivariate Analysis (MVA) of codon usage. The MVA method employed in CodonW is correspondence analysis (COA) (the most popular MVA method for codon usage analysis). CodonW can generate a COA for codon usage, relative synonymous codon usage or amino acid usage. Additional analyses of codon usage include investigation of optimal codons, codon and dinucleotide bias, and/or base composition. CodonW analyses sequences encoded by genetic codes other than the universal code.

Please cite: Variation in the strength of selected codon usage bias among bacteria.. (PubMed,eprint) Nucleic Acids Research 33(4):1141-1153 (2005)
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Concavity
Vorhersage von Proteinliganden-Bindungsstellen mittels Struktur und Konservierung
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ConCavity sagt Bindungsstellen von Proteinliganden voraus, indem die evolutionäre Sequenzkonservierung und dreidimensionale Struktur verbunden werden.

ConCavity akzeptiert als Eingabe das Proteinstrukturformat PDB und optional Dateien, die die evolutionäre Sequenzkonservierung der Ketten in der Strukturdatei charakterisieren.

Die folgenden Resultatdateien werden standardmäßig erstellt:

  • Vorhersagen von Rest-Ligandenbindung für jede Kette (*.scores).
  • Vorhersagen von Rest-Ligandenbindung in einer Datei des Formats PDB (Rest-Scores sind im temorären »factor«-Feld platziert, *_residue.pdb).
  • Vorhersage von Bindungstaschen in einer Datei des Formats DX (*.dx).
  • PyMOL-Skript um die Vorhersagen zu visualisieren (*.pml).
The package is enhanced by the following packages: conservation-code
Please cite: John A. Capra, Roman A. Laskowski, Janet M. Thornton, Mona Singh and Thomas A. Funkhouser: Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure. (PubMed) PLoS Computational Biology 5(12):e1000585 (2009)
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Conservation-code
Werkzeug zur Bewertung von Proteinsequenz-Konservierung
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Das Paket stellt das Werkzeug score_conservation(1) bereit, das die Konservierung bei Proteinsequenzen bewertet.

Die folgenden Bewertungsmethoden für Konservierungen sind implementiert:

  • Summe aller Paare
  • gewichtete Summe aller Paare
  • Shannon-Entropie
  • Shannon-Entropie nach Eigenschaften gruppiert (Mirny und Shakhnovich 1995, Valdar und Thornton 2001)
  • relative Entropie nach Eigenschaften gruppiert (Williamson 1995)
  • von-Neumann-Entropie (Caffrey et al 2004)
  • relative Entropie (Samudrala und Wang 2006)
  • Jensen–Shannon-Divergenz (Capra und Singh 2007)

Ebenso enthalten ist eine fensterbasierte Erweiterung, die die geschätzte Konservierung von sequenziell ähnlichen Resten in den Score für jede Spalte einarbeitet. Diese Fensterfunktion kann auf jede der genannten Bewertungsmethoden angewandt werden.

Das Programm akzeptiert Alignments in den Formaten CLUSTAL und FASTA.

Die sequenzspezifische Ausgabe kann auch als Eingabe der Konservierung für ConCavitiy verwendet werden.

Konservierung trifft beim Identifizieren von aktiven Zentren und Resten in der Nähe von gebundenen Liganden gute Voraussagen.

Please cite: John A. Capra and Mona Singh: Predicting functionally important residues from sequence conservation. (PubMed) Bioinformatics 23(15):1875-82 (2007)
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Crac
integrated RNA-Seq read analysis
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CRAC is a tool to analyze High Throughput Sequencing (HTS) data in comparison to a reference genome. It is intended for transcriptomic and genomic sequencing reads. More precisely, with transcriptomic reads as input, it predicts point mutations, indels, splice junction, and chimeric RNAs (ie, non colinear splice junctions). CRAC can also output positions and nature of sequence error that it detects in the reads. CRAC uses a genome index. This index must be computed before running the read analysis. For this sake, use the command "crac-index" on your genome files. You can then process the reads using the command crac. See the man page of CRAC (help file) by typing "man crac". CRAC requires large amount of main memory on your computer. For processing against the Human genome, say 50 million reads of 100 nucleotide each, CRAC requires about 40 gigabytes of main memory. Check whether the system of your computing server is equipped with sufficient amount of memory before launching an analysis.

Please cite: Eliseos J. Mucaki, Natasha G. Caminsky, Ami M. Perri, Ruipeng Lu, Alain Laederach, Matthew Halvorsen, Joan H. M. Knoll and Peter K. Rogan: A unified analytic framework for prioritization of non-coding variants of uncertain significance in heritable breast and ovarian cancer. (PubMed) BMS Medical Genomics 9:19 (2016)
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Csb
Computational Structural Biology Toolbox (CSB)
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Computational Structural Biology Toolbox (CSB) is a Python class library for reading, storing and analyzing biomolecular structures in a variety of formats with rich support for statistical analyses.

CSB is designed for reusability and extensibility and comes with a clean, well-documented API following good object-oriented engineering practice.

This package contains some user executable tools.

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Cutadapt
Clean biological sequences from high-throughput sequencing reads
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Cutadapt helps with biological sequence clean tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

This package contains the user interface.

Please cite: Marcel Martin: Cutadapt removes adapter sequences from high-throughput sequencing reads. (eprint) EMBnet.journal 17(1):10-12 (2015)
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Daligner
local alignment discovery between long nucleotide sequencing reads
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These tools permit one to find all significant local alignments between reads encoded in a Dazzler database. The assumption is that the reads are from a Pacific Biosciences RS II long read sequencer. That is, the reads are long and noisy, up to 15% on average.

Please cite: Gene Myers: Efficient Local Alignment Discovery amongst Noisy Long Reads. 8701:52-67 (2014)
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Datamash
statistics tool for command-line interface
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GNU Datamash is a command-line program which performs basic numeric, textual and statistical operations on input textual data files. It is designed to be portable and reliable, and aid researchers to easily automate analysis pipelines, without writing code or even short scripts.

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Dawg
simulate the evolution of recombinant DNA sequences
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DNA Assembly with Gaps (Dawg) is an application designed to simulate the evolution of recombinant DNA sequences in continuous time based on the robust general time reversible model with gamma and invariant rate heterogeneity and a novel length-dependent model of gap formation. The application accepts phylogenies in Newick format and can return the sequence of any node, allowing for the exact evolutionary history to be recorded at the discretion of users. Dawg records the gap history of every lineage to produce the true alignment in the output. Many options are available to allow users to customize their simulations and results.

Please cite: Reed A. Cartwright: DNA assembly with gaps (Dawg): simulating sequence evolution. (PubMed,eprint) Bioinformatics 21(Suppl 3):iii31-iii38 (2005)
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Dazzdb
manage nucleotide sequencing read data
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To facilitate the multiple phases of the dazzler assembler, all the read data is organized into what is effectively a database of the reads and their meta-information. The design goals for this data base are as follows:

  • The database stores the source Pacbio read information in such a way that it can re-create the original input data, thus permitting a user to remove the (effectively redundant) source files. This avoids duplicating the same data, once in the source file and once in the database.
  • The data base can be built up incrementally, that is new sequence data can be added to the data base over time.
  • The data base flexibly allows one to store any meta-data desired for reads. This is accomplished with the concept of tracks that implementors can add as they need them.
  • The data is held in a compressed form equivalent to the .dexta and .dexqv files of the data extraction module. Both the .fasta and .quiva information for each read is held in the data base and can be recreated from it. The .quiva information can be added separately and later on if desired.
  • To facilitate job parallel, cluster operation of the phases of the assembler, the database has a concept of a current partitioning in which all the reads that are over a given length and optionally unique to a well, are divided up into blocks containing roughly a given number of bases, except possibly the last block which may have a short count. Often programs can be run on blocks or pairs of blocks and each such job is reasonably well balanced as the blocks are all the same size. One must be careful about changing the partition during an assembly as doing so can void the structural validity of any interim block-based results.
Deepnano
alternative basecaller for MinION reads of genomic sequences
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DeepNano is alternative basecaller for Oxford Nanopore MinION reads based on deep recurrent neural networks.

Currently it works with SQK-MAP-006 and SQK-MAP-005 chemistry and as a postprocessor for Metrichor.

Please cite: Vladimír Boža, Broňa Brejová and Tomáš Vinař: DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads. PLOS one (2017)
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Remark of Debian Med team: There is no intend to keep continue the existing packaging since

the program nanocall seems to serve the intended purpose better

Delly
Structural variant discovery by read analysis
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Delly performs Structural variant discovery by integrated paired-end and split-read analysis. It discovers, genotypes and visualizes deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. It uses paired-ends, split-reads and read-depth to sensitively and accurately delineate genomic rearrangements throughout the genome.

Please cite: Tobias Rausch, Thomas Zichner, Andreas Schlattl, Adrian M. Stuetz, Vladimir Benes and Jan O. Korbel: DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28:i333-i339 (2012)
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Dialign
Segmentbasiertes multiples Sequenzalignment
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Das Kommandozeilenwerkzeug DIALIGN2 führt ein multiples Alignment von Protein- oder DNA-Sequenzen aus. Es erstellt Alignments aus gap-freien Paaren von ähnlichen Sequenzsegmenten. Dieses Bewertungsverfahren ist der grundlegende Unterschied zwischen DIALIGN und anderen globalen oder lokalen Methoden für Sequenzalignments. Beachten Sie, dass DIALIGN bei Gaps das Ergebnis nicht schlechter bewertet.

Please cite: Burkhard Morgenstern: DIALIGN 2: improvement of the segment-to-segment approach to multiple sequence alignment. (PubMed,eprint) Bioinformatics 15(3):211-218 (1999)
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Dialign-tx
Segmentbasiertes multiples Sequenzalignment
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DIALIGN-TX ist ein Kommandozeilenwerkzeug, um mehrere Protein- oder DNA-Sequenzen aneinander auszurichten (»zu alignen«). Es handelt sich um eine vollständige Reimplementation des segmentbasierten Ansatzes, einschließlich einiger neuer Verbesserungen und Heuristiken und anderer Verbesserungen, die im Vergleich mit DIALIGN 2.2 oder DIALIGN-T deutlich die Qualität der ermittelten Alignments erhöht. Für paarweise Alignments nutzt DIALIGN-TX einen Algorithmus zur Verkettung von Fragmenten, der Ketten niedrig bewerteter lokaler Alignments den isolierten höher bewerteten Fragmenten vorzieht. Für multiple Alignments nutzt DIALIGN-TX eine verbesserte, erfolgshungrige Prozedur, die nicht auf falsche lokale Sequenzähnlichkeiten hereinfällt.

The package is enhanced by the following packages: dialign-tx-data
Please cite: Amarendran R. Subramanian, Michael Kaufmann and Burkhard Morgenstern: DIALIGN-TX: greedy and progressive approaches for segment-based multiple sequence alignment. (PubMed) Algorithms for Molecular Biology 3(1):6 (2008)
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Diamond-aligner
accelerated BLAST compatible local sequence aligner
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DIAMOND is a sequence aligner for protein and translated DNA searches and functions as a drop-in replacement for the NCBI BLAST software tools. It is suitable for protein-protein search as well as DNA-protein search on short reads and longer sequences including contigs and assemblies, providing a speedup of BLAST ranging up to x20,000.

Please cite: Benjamin Buchfink, Chao Xie and Daniel H Huson: Fast and sensitive protein alignment using DIAMOND. (PubMed) Nature methods 12(1):59-60 (2015)
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Dindel
determines indel calls from short-read data
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Dindel is a program for calling small indels from short-read sequence data ('next generation sequence data'). It currently is designed to handle only Illumina data.

Dindel requires a BAM file containing the read-alignments as input. It then extracts candidate indels from the BAM file, and realigns the reads to candidate haplotypes consisting of these candidate indels. If there is sufficient evidence for an alternative haplotype to the reference, it will call an indel.

It is possible to test indels discovered with other methods using Dindel, for instance longer indels obtained through assembly methods. Dindel will then realign both mapped and unmapped reads to see if the candidate indel is supported by the reads.

Dindel outputs both genotype likelihoods and includes a script to convert these to a VCF file with indel and SNP calls.

There is basic support for outputting realigned BAM files for each realignment-window. These realigned BAM files can be used to call SNPs near (candidate) indels.

Please cite: Cornelis A. Albers, Gerton Lunter, Daniel G. MacArthur, Gilean McVean, Willem H. Ouwehand and Richard Durbin: Dindel: Accurate indel calls from short-read data. (PubMed,eprint) Genome Research 21(6):961-973 (2010)
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Discosnp
discovering Single Nucleotide Polymorphism from raw set(s) of reads
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Software discoSnp is designed for discovering Single Nucleotide Polymorphism (SNP) from raw set(s) of reads obtained with Next Generation Sequencers (NGS).

Note that number of input read sets is not constrained, it can be one, two, or more. Note also that no other data as reference genome or annotations are needed.

The software is composed by two modules. First module, kissnp2, detects SNPs from read sets. A second module, kissreads, enhance the kissnp2 results by computing per read set and for each found SNP:

 1) its mean read coverage
 2) the (phred) quality of reads generating the polymorphism.

This program is superseded by DiscoSnp++.

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Disulfinder
Vorhersage der Disulfidbindungen von Cysteinen und deren Verbindungsfähigkeit
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»disulfinder« soll die Disulfidbindungen von Cysteinen und deren Disulfid-Verbindungsfähigkeit aus der Sequenz allein voraussagen. Disulfidbrücken spielen eine große Rolle in der Stabilisierung des Faltungsprozesses von verschiedenen Proteinen. Die Voraussage von Disulfidbrücken aus der Sequenz allein ist daher für das Studium der strukturellen und funktionalen Eigenschaften von bestimmten Proteinen nützlich. Zusätzlich kann Wissen über die Disulfidbindungen von Cysteinen bei der experimentellen Strukturbestimmung helfen und in anderen genomischen Annotationsaufgaben nützlich sein.

»disulfinder« sagt Disulfidmuster in zwei Berechnungsschritten voraus: (1) die Disulfidbindungen jedes Cysteins werden von einem binären Klassifikator (BRNN-SVM) vorausgesagt; (2) Cysteine, bei denen man weiß, dass sie an der Brückenbildung teilhaben, werden von einem rekurrenten neuronalen Netz gepaart, um ein Muster der Verbindungsfähigkeit zu erhalten.

Please cite: Alessio Ceroni, Andrea Passerini, Alessandro Vullo and Paolo Frasconi: DISULFIND: a disulfide bonding state and cysteine connectivity prediction server. (PubMed) Nucleic Acids Res 34(Web Server issue):W177-81 (2006)
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Dnaclust
tool for clustering millions of short DNA sequences
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dnaclust is a tool for clustering large number of short DNA sequences. The clusters are created in such a way that the "radius" of each clusters is no more than the specified threshold.

The input sequences to be clustered should be in Fasta format. The id of each sequence is based on the first word of the seqeunce in the Fasta format. The first word is the prefix of the header up to the first occurrence of white space characters in the header.

Please cite: Mohammadreza Ghodsi, Bo Liu and Mihai Pop: DNACLUST: accurate and efficient clustering of phylogenetic marker genes. (PubMed,eprint) BMC Bioinformatics 12:271 (2011)
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Dotter
detailed comparison of two genomic sequences
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Dotter is a graphical dot-matrix program for detailed comparison of two sequences.

  • Every residue in one sequence is compared to every residue in the other, and a matrix of scores is calculated.
  • One sequence is plotted on the x-axis and the other on the y-axis.
  • Noise is filtered out so that alignments appear as diagonal lines.
  • Pairwise scores are averaged over a sliding window to make the score matrix more intelligible.
  • The averaged score matrix forms a three-dimensional landscape, with the two sequences in two dimensions and the height of the peaks in the third. This landscape is projected onto two dimensions using a grey-scale image - the darker grey of a peak, the higher the score is.
  • The contrast and threshold of the grey-scale image can be adjusted interactively, without having to recalculate the score matrix.
  • An Alignment Tool is provided to examine the sequence alignment that the grey-scale image represents.
  • Known high-scoring pairs can be loaded from a GFF file and overlaid onto the plot.
  • Gene models can be loaded from GFF and displayed alongside the relevant axis.
  • Compare a sequence against itself to find internal repeats.
  • Find overlaps between multiple sequences by making a dot-plot of all sequences versus themselves.
  • Run Dotter in batch mode to create large, time-consuming dot-plots as a background process.
Please cite: Gemma Barson and Ed Griffiths: SeqTools: visual tools for manual analysis of sequence alignments. (PubMed,eprint) BMC Research Notes 9:39 (2016)
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Dssp
Sekundärstruktur-Zuordnung bei Proteinen, basierend auf 3D-Struktur
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Mit dem Programm DSSP können Sie die Sekundärstruktur eines Proteins basierend auf der gelösten dreidimensionalen (3D-)Struktur zuordnen.

Diese neu geschriebene DSSP-Version (2) erstellt die gleiche Ausgabe wie das originale DSSP, geht jedoch besser mit Ausnahmen in PDB-Dateien um und ist viel schneller.

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Dwgsim
short sequencing read simulator
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DWGSIM simulates short sequencing reads from modern sequencing platforms. DWGSIM generates base error rates using a parametric model, allowing a more realisic error profile. It was originally developed for use in evaluating short read aligners.

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E-mem
Efficient computation of Maximal Exact Matches for very large genomes
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E-MEM enables efficient computation of Maximal Exact Matches (MEMs) that does not use full text indexes. The algorithm uses much less space and is highly amenable to parallelization. It can compute all MEMs of minimum length 100 between the whole human and mouse genomes on a 12 core machine in 10 min and 2 GB of memory; the required memory can be as low as 600 MB. It can run efficiently genomes of any size. Extensive testing and comparison with currently best algorithms is provided.

Mummer has many different scripts where one of the key program is MEM computation. In all the scripts, the MEM computation program can be replaced with e-mem with ease for better performance.

Please cite: Nilesh Khiste and Lucian Ilie: E-MEM: efficient computation of maximal exact matches for very large genomes. (PubMed,eprint) Bioinformatics 31(4):509-514 (2015)
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Ea-utils
command-line tools for processing biological sequencing data
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Ea-utils provides a set of command-line tools for processing biological sequencing data, barcode demultiplexing, adapter trimming, etc.

Primarily written to support an Illumina based pipeline - but should work with any FASTQs.

Main Tools are:

  • fastq-mcf Scans a sequence file for adapters, and, based on a log-scaled threshold, determines a set of clipping parameters and performs clipping. Also does skewing detection and quality filtering.

  • fastq-multx Demultiplexes a fastq. Capable of auto-determining barcode id's based on a master set fields. Keeps multiple reads in-sync during demultiplexing. Can verify that the reads are in-sync as well, and fail if they're not.

  • fastq-join Similar to audy's stitch program, but in C, more efficient and supports some automatic benchmarking and tuning. It uses the same "squared distance for anchored alignment" as other tools.

  • varcall Takes a pileup and calculates variants in a more easily parameterized manner than some other tools.

Please cite: Erik Aronesty: Comparison of Sequencing Utility Programs. (eprint) The Open Bioinformatics Journal 7:1-8 (2013)
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Ecopcr
Abschätzen der Qualität von PCR-Barcode-Primern
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DNA-Barcoding ist ein Werkzeug zur Charakterisierung des Spezienursprungs unter Verwendung einer kurzen Sequenz von einer vereinbarten Standardposition im Genom. Für die Verwendung als DNA-Barcode sollte der betrachtete Genomabschnitt von Individuen der gleichen Spezies nur in einem geringen Maße variieren, wohingegen bei Individuen unterschiedlicher Spezies eine ausgeprägte Variation vorliegen sollte. Für eine praktische Anwendungsweise sollte der Genomabschnitt von zwei konservierten Regionen flankiert sein, um eine Erstellung von PCR-Primern zu ermöglichen. Mehrere manuell entdeckte Barcode-Loci, wie COI, rbcL, 18S, 16S und 23S rDNA, oder trnH-ps finden heutzutage routinemäßige Verwendung. Allerdings wurde noch keine objektive Funktion beschrieben, mit deren Hilfe die Qualität bezüglich Allgemeingültigkeit (»barcode coverage, Bc«) oder bezüglich der Fähigkeit taxonomischer Unterscheidung (»barcode specificity, Bs«) quantifiziert werden kann.

ecoPCR ist eine von LECA und dem Helix-Projekt entwickelte elektronische PCR-Software. Diese hilft bei der Abschätzung der Qualität von PCR-Barcode-Primern. In Verbindung mit den OBITools können ecoPCR-Ausgaben nachbearbeitet und somit »barcode coverage« und »barcode specificity« berechnet werden. Neue Barcode-Primer können unter Verwendung der Software ecoPrimers entwickelt werden.

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Edtsurf
Triangulierte Gitteroberflächen für Proteinstrukturen
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Mit dem quelloffenen Programm EDTSurf können triangulierte Oberflächen für Makromoleküle konstruiert werden. Es erstellt drei grundlegende Makromoleküloberflächen: Van-der-Waals-Oberfläche, lösungsmittelzugängliche Oberfläche (»solvent-accessible surface«) und Connolly-Oberfläche (»solvent-excluded surface«). EDTsurf identifiziert auch Kavitäten im Inneren von Makromolekülen.

Please cite: Dong Xu and Yang Zhang: Generating Triangulated Macromolecular Surfaces by Euclidean Distance Transform.. (PubMed,eprint) PLoS ONE 4(12):e8140 (2009)
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Eigensoft
reduction of population bias for genetic analyses
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The EIGENSOFT package combines functionality from the group's population genetics methods (Patterson et al. 2006) and their EIGENSTRAT stratification method (Price et al. 2006). The EIGENSTRAT method uses principal components analysis to explicitly model ancestry differences between cases and controls along continuous axes of variation; the resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. The EIGENSOFT package has a built-in plotting script and supports multiple file formats and quantitative phenotypes.

Please cite: Alkes L. Price, Nick J. Patterson, Robert M. Plenge, Michael E. Weinblatt, Nancy A. Shadick and David Reich: Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics 38:904 - 909 (2006)
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Elph
DNA/protein sequence motif finder
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ELPH (Estimated Locations of Pattern Hits) is a general-purpose Gibbs sampler for finding motifs in a set of DNA or protein sequences. The program takes as input a set containing anywhere from a few dozen to thousands of sequences, and searches through them for the most common motif, assuming that each sequence contains one copy of the motif. We have used ELPH to find patterns such as ribosome binding sites (RBSs) and exon splicing enhancers (ESEs).

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Embassy-domainatrix
Zusätzliche EMBOSS-Kommandos zur Arbeit mit Domänen-Klassendateien
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Die DOMAINATRIX-Programme wurden von Jon Ison und Kollegen am MRC HGMP für ihre Forschung im Bereich der Proteine entwickelt. Diese sind in einem Paket nammens EMBASSY enthalten, welches z.Z. in Arbeit ist.

Anwendungen der aktuellen Veröffentlichung von domainatrix sind cathparse (generiert DCF-Dateien von »raw«-CATH-Dateien), domainnr (entfernt redundante Bereiche aus einer DCF-Datei), domainreso (entfernt Bereiche niedriger Auflösung einer DCF-Datei), domainseqs (fügt Sequenzeinträge zu einer DCF-Datei hinzu), domainsse (fügt weitere Struktureinträge zu einer DCF-Datei hinzu), scopparse (generiert eine DCF-Datei aus »raw«-SCOP-Dateien) und ssematch (sucht in einer DCF-Datei nach weiteren Strukturübereinstimmungen).

Embassy-domalign
Zusätzliche EMBOSS-Befehle für Alignments mit Proteindomänen
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Die DOMALIGN-Programme wurden von Jon Ison et al. am MRC HGMP für deren Forschung im Bereich der Proteindomänen entwickelt. Diese Programme sind als ein EMBASSY-Paket enthalten, die Entwicklung ist jedoch noch nicht abgeschlossen.

Anwendungen der aktuellen domalign-Veröffentlichung sind allversusall (Daten von Sequenzähnlichkeiten von einem Alle-gegen-Alle-Vergleich), domalign (erstellt Alignments (DAF-Datei) für Knoten in einer DCF-Datei), domainrep (sortiert DCF-Dateien neu, um repräsentative Strukturen zu identifizieren) und seqalign (erweitert Alignments (DAF-Datei) mit Sequenzen (DHF-Datei)).

Embassy-domsearch
Zusätzliche EMBOSS-Befehle zur Suche von Proteindomänen
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Die DOMSEARCH-Programme wurden von Jon Ison und Kollegen am MRC HGMP für ihre Forschung an Proteindomänen entwickelt. Sie sind im EMBASSY-Paket als Programme in Entwicklung enthalten.

Anwendungen in dieser Veröffentlichung von DOMSEARCH sind seqfraggle (entfernt Fragmentsequenzen aus DHF-Dateien), seqnr (entfernt Redundanzen aus DHF-Dateien), seqsearch (erstellt PSI-BLAST-Treffer (DHF-Datei) aus einer DAF-Datei), seqsort (entfernt mehrdeutig klassifizierte Sequenzen aus DHF-Dateien) und seqwords (erstellt DHF-Dateien aus einer Schlagwort-Suche bei UniProt).

Emboss
European molecular biology open software suite
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EMBOSS is a free Open Source software analysis package specially developed for the needs of the molecular biology (e.g. EMBnet) user community. The software automatically copes with data in a variety of formats and even allows transparent retrieval of sequence data from the web. Also, as extensive libraries are provided with the package, it is a platform to allow other scientists to develop and release software in true open source spirit. EMBOSS also integrates a range of currently available packages and tools for sequence analysis into a seamless whole. EMBOSS breaks the historical trend towards commercial software packages.

The package is enhanced by the following packages: clustalw primer3
Please cite: Peter Rice, Ian Longden and Alan Bleasby: EMBOSS: The European Molecular Biology Open Software Suite. (PubMed) Trends in Genetics 16(6):276 - 277 (2000)
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Examl
Exascale Maximum Likelihood (ExaML) code for phylogenetic inference
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Exascale Maximum Likelihood (ExaML) is a code for phylogenetic inference using MPI. This code implements the popular RAxML search algorithm for maximum likelihood based inference of phylogenetic trees.

ExaML is a strapped-down light-weight version of RAxML for phylogenetic inference on huge datasets. It can only execute some very basic functions and is intended for computer-savvy users that can write little perl-scripts and have experience using queue submission scripts for clusters. ExaML only implements the CAT and GAMMA models of rate heterogeneity for binary, DNA, and protein data.

ExaML uses a radically new MPI parallelization approach that yields improved parallel efficiency, in particular on partitioned multi-gene or whole-genome datasets. It also implements a new load balancing algorithm that yields better parallel efficiency.

It is up to 4 times faster than its predecessor RAxML-Light and scales to a larger number of processors.

Please cite: Alexey M. Kozlov, Andre J. Aberer and Alexandros Stamatakis: ExaML version 3: a tool for phylogenomic analyses on supercomputers. (PubMed,eprint) Bioinformatics 31(15):2577-2579 (2015)
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Exonerate
Generisches Werkzeug zum paarweisen Sequenzvergleich
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Mit Exonerate können Sie Sequenzen ab- und vergleichen. Das Programm bietet Ihnen viele Alignment-Modelle, welche entweder vollständig dynamische Programmierung oder eine Reihe von heuristischen Methoden verwenden. Ein Großteil der Funktionalität der »Wise dynamic programming suite« wurde zur Erhöhung der Effizienz in C neu geschrieben. Exonerate ist eine wesentliche Komponente bei der Erstellung der »Ensembl Genome«-Datenbanken, die Ähnlichkeitsmaße für RNA- und DNA-Sequenzen bestimmt und so allgemein »splice variants« und Codesequenzen bestimmt.

Ein »In-silico PCR«-System zur Simulation von Experimenten (Siehe auch das Handbuch von »ipcress«) wird zusammen mit »exonerate« verteilt.

Dieses Paket beinhaltet auch eine Auswahl an Werkzeugen zur Erstellung einfacher, schneller Änderungen an »fasta«-Dateien mit über 2GB Dateigröße.

Please cite: Guy C. Slater and Ewan Birney: Automated generation of heuristics for biological sequence comparison. (PubMed,eprint) BMC Bioinformatics 6(1):31 (2005)
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Falcon
diploid-aware genome assembly of single-molecule sequencing reads
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FALCON is a set of tools for fast aligning long reads for consensus and assembly. It is a simple code collection for efficient assembly of haploid and diploid genomes.

Please cite: Chen-Shan Chin, Paul Peluso, Fritz J Sedlazeck, Maria Nattestad, Gregory T Concepcion, Alicia Clum, Christopher Dunn, Ronan O'Malley, Rosa Figueroa-Balderas, Abraham Morales-Cruz, Grant R Cramer, Massimo Delledonne, Chongyuan Luo, Joseph R Ecker, Dario Cantu, David R Rank and Michael C Schatz": Phased diploid genome assembly with single-molecule real-time sequencing. (PubMed) Nature Methods (2016)
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Fastahack
utility for indexing and sequence extraction from FASTA files
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fastahack is a small application for indexing and extracting sequences and subsequences from FASTA files. The included Fasta.cpp library provides a FASTA reader and indexer that can be embedded into applications which would benefit from directly reading subsequences from FASTA files. The library automatically handles index file generation and use.

Features:

  • FASTA index (.fai) generation for FASTA files
  • Sequence extraction
  • Subsequence extraction
  • Sequence statistics (currently only entropy is provided)

Sequence and subsequence extraction use fseek64 to provide fastest-possible extraction without RAM-intensive file loading operations. This makes fastahack a useful tool for bioinformaticists who need to quickly extract many subsequences from a reference FASTA sequence.

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Fastaq
FASTA and FASTQ file manipulation tools
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Fastaq represents a diverse collection of scripts that perform useful and common FASTA/FASTQ manipulation tasks, such as filtering, merging, splitting, sorting, trimming, search/replace, etc. Input and output files can be gzipped (format is automatically detected) and individual Fastaq commands can be piped together.

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Fastdnaml
Werkzeug zum Aufbau phylogenetischer Bäume von DNA-Sequenzen
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FastDNAml ist abgeleitet von Joseph Felsensteins DNAML Version 3.3 (Teil seines Pakets PHYLIP). Bevor Sie fastDNAml verwenden, sollten Sie die Dokumentation für DNAML heranziehen.

FastDNAml ist der Versuch, das gleiche Problem wie DNAML effektiver zu lösen, damit größere Bäume und/oder »bootstrap«-Replikate behandelt werden können. Bei großen Teilen von fastDNAml handelt es sich lediglich um eine Neuprogrammierung der in Pascal geschriebenen PHYLIP DNAML Version 3.3 in der Sprache C.

Beachten Sie, dass die Webseite dieses Programms nicht mehr verfügbar ist und dieses Programm daher wahrscheinlich nicht mehr aktualisiert wird.

Please cite: Gary J. Olsen, Hideo Matsuda, Ray Hagstrom and Ross Overbeek: fastDNAml: a tool for construction of phylogenetic trees of DNA sequences using maximum likelihood. (PubMed,eprint) Comput Appl Biosci 10(1):41-48 (1994)
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Fastlink
Schnellere Version der Stammbaum-Programme von Linkage
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Genkopplungsanalyse ist ein statistisches Verfahren, das zum Abbilden von Genen und zum Auffinden wahrscheinlicher Positionen von Erbfehlern verwendet wird. Es gab ein Standard-Softwarepaket zur Genkopplung namens LINKAGE. FASTLINK ist eine deutlich veränderte und verbesserte Variante der Hauptprogramme von LINKAGE. Diese laufen sequenziell deutlich schneller, können parallelisiert werden, lassen sich nach einem Computerabsturz elegant wiederherstellen und enthalten reichlich neue Dokumentationen. FASTLINK wurde in über 1000 veröffentlichten Genkopplungsstudien verwendet.

Dieses Paket enthält die folgenden Programme:

 ilink:    Optimierungsprozedur GEMINI, um einen lokal optimalen Wert
           des Theta-Vektors von Rekombinationsanteilen zu bestimmen.
 linkmap:  berechnet die Positionswertung eines Locus gegenüber einer
           Sammlung von anderen Loci.
 lodscore: vergleicht Wahrscheinlichkeiten auf lokal optimalen Theta.
 mlink:    berechnet die LOD-Scores und Risiken mit zwei oder mehreren
           Loci.
 unknown:  identifiziert mögliche Genotypen für unbekannte Personen.
Please cite: R. W. Cottingham Jr., R. M. Idury and A. A. Schaffer: Faster Sequential Genetic Linkage Computations. (PubMed,eprint) American Journal of Human Genetics 53(1):252-263 (1993)
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Fastml
maximum likelihood ancestral amino-acid sequence reconstruction
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FastML is a bioinformatics tool for the reconstruction of ancestral sequences based on the phylogenetic relations between homologous sequences. FastML runs several algorithms that reconstruct the ancestral sequences with emphasis on an accurate reconstruction of both indels and characters. For character reconstruction the previously described FastML algorithms are used to efficiently infer the most likely ancestral sequences for each internal node of the tree. Both joint and the marginal reconstructions are provided. For indels reconstruction the sequences are first coded according to the indel events detected within the multiple sequence alignment (MSA) and then a state-of-the-art likelihood model is used to reconstruct ancestral indels states. The results are the most probable sequences, together with posterior probabilities for each character and indel at each sequence position for each internal node of the tree. FastML is generic and is applicable for any type of molecular sequences (nucleotide, protein, or codon sequences).

Please cite: Haim Ashkenazy, Osnat Penn, Adi Doron-Faigenboim, Ofir Cohen, Gina Cannarozzi, Oren Zomer and Tal Pupko: FastML: a web server for probabilistic reconstruction of ancestral sequences. (PubMed,eprint) Nucleic Acids Research 40(Web Server issue):W580-W584 (2012)
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Fastqc
quality control for high throughput sequence data
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FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.

The main functions of FastQC are

  • Import of data from BAM, SAM or FastQ files (any variant)
  • Providing a quick overview to tell you in which areas there may be problems
  • Summary graphs and tables to quickly assess your data
  • Export of results to an HTML based permanent report
  • Offline operation to allow automated generation of reports without running the interactive application
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Fastqtl
Quantitative Trait Loci (QTL) mapper in cis for molecular phenotypes
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The goal of FastQTL is to identify single-nucleotide polymorphisms (SNPs) which are significantly associated with various molecular phenotypes (i.e. expression of known genes, cytosine methylation levels, etc). It performs scans for all possible phenotype-variant pairs in cis (i.e. variants located within a specific window around a phenotype). FastQTL implements a new permutation scheme (Beta approximation) to accurately and rapidly correct for multiple-testing at both the genotype and phenotype levels.

The package is enhanced by the following packages: fastqtl-doc
Please cite: Halit Ongen, Alfonso Buil, Andrew Anand Brown, Emmanouil T. Dermitzakis and and Olivier Delaneau: Fast and efficient QTL mapper for thousands of molecular phenotypes. (eprint) Bioinformatics (2015)
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Fasttree
phylogenetic trees from alignments of nucleotide or protein sequences
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FastTree infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. It handles alignments with up to a million of sequences in a reasonable amount of time and memory. For large alignments, FastTree is 100-1,000 times faster than PhyML 3.0 or RAxML 7.

FastTree is more accurate than PhyML 3 with default settings, and much more accurate than the distance-matrix methods that are traditionally used for large alignments. FastTree uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT (Jones-Taylor-Thornton 1992) model of amino acid evolution. To account for the varying rates of evolution across sites, FastTree uses a single rate for each site (the "CAT" approximation). To quickly estimate the reliability of each split in the tree, FastTree computes local support values with the Shimodaira-Hasegawa test (these are the same as PhyML 3's "SH-like local supports").

This package contains a single threaded version (fasttree) and a parallel version which uses OpenMP (fasttreMP).

Please cite: Morgan N. Price, Paramvir S. Dehal and Adam P. Arkin: FastTree 2 -- Approximately Maximum-Likelihood Trees for Large Alignments.. (PubMed,eprint) PLoS ONE 5(3):e9490 (2010)
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Fastx-toolkit
Vorverarbeitung kurzer FASTQ/A-Nukleotidsequenzen
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FASTX-Toolkit ist eine Sammlung an Befehlszeilenwerkzeugen zur Vorverarbeitung von kurzen Nukleotidsequenzen im FASTA- oder FASTQ-Format, die üblicherweise von Sequenzierautomaten der nächsten Generation erstellt werden. Die Hauptverarbeitung solcher FASTA/FASTQ-Dateien ist das Alignieren der Sequenzen zu Referenzgenomen oder anderen Datenbanken, mittels spezialisierter Programme wie BWA, Bowtie und vielen anderen. Jedoch ist es manchmal produktiver die FASTA/FASTQ-Dateien zu vorverarbeiten, bevor die Sequenzen zum Genom angeordnet werden. Es werden also Sequenzen manipuliert, um bessere Resultate zu erhalten. Die Werkzeuge des FASTX-Toolkits führen einige dieser Vorverarbeitungen durch.

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Ffindex
simple index/database for huge amounts of small files
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FFindex is a very simple index/database for huge amounts of small files. The files are stored concatenated in one big data file, separated by '\0'. A second file contains a plain text index, giving name, offset and length of the small files. The lookup is currently done with a binary search on an array made from the index file.

This package provides the executables.

Figtree
Grafischer Betrachter für phylogenetische Bäume
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FigTree ist gedacht als grafischer Betrachter für phylogenetische Bäume und als ein Programm, das veröffentlichungsreife Abbildungen erstellt. Insbesondere ist es für die Anzeige zusammengefasster und annotierter Bäume geeignet, die von BEAST erstellt wurden.

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Fitgcp
fitting genome coverage distributions with mixture models
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Genome coverage, the number of sequencing reads mapped to a position in a genome, is an insightful indicator of irregularities within sequencing experiments. While the average genome coverage is frequently used within algorithms in computational genomics, the complete information available in coverage profiles (i.e. histograms over all coverages) is currently not exploited to its full extent. Thus, biases such as fragmented or erroneous reference genomes often remain unaccounted for. Making this information accessible can improve the quality of sequencing experiments and quantitative analyses.

fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm.

Please cite: Martin S. Lindner, Maximilian Kollock, Franziska Zickmann and Bernhard Y. Renard: Analyzing genome coverage profiles with applications to quality control in metagenomics. (PubMed,eprint) Bioinformatics 29(10):1260-1267 (2013)
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Flexbar
flexible barcode and adapter removal for sequencing platforms
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Flexbar preprocesses high-throughput sequencing data efficiently. It demultiplexes barcoded runs and removes adapter sequences. Moreover, trimming and filtering features are provided. Flexbar increases mapping rates and improves genome and transcriptome assemblies. It supports next-generation sequencing data in fasta/q and csfasta/q format from Illumina, Roche 454, and the SOLiD platform.

Parameter names changed in Flexbar. Please review scripts. The recent months, default settings were optimised, several bugs were fixed and various improvements were made, e.g. revamped command-line interface, new trimming modes as well as lower time and memory requirements.

Please cite: Matthias Dodt, Johannes T. Roehr, Rina Ahmed and Christoph Dieterich: FLEXBAR — Flexible Barcode and Adapter Processing for Next-Generation Sequencing Platforms. (eprint) Biology 1(3):895-905 (2012)
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Fml-asm
tool for assembling Illumina short reads in small regions
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Fml-asm is a command-line tool for assembling Illumina short reads in regions from 100bp to 10 million bp in size, based on the fermi-lite library. It is largely a light-weight in-memory version of fermikit without generating any intermediate files. It inherits the performance, the relatively small memory footprint and the features of fermikit. In particular, fermi-lite is able to retain heterozygous events and thus can be used to assemble diploid regions for the purpose of variant calling.

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Freebayes
Bayesian haplotype-based polymorphism discovery and genotyping
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FreeBayes is a Bayesian genetic variant detector designed to find small polymorphisms, specifically SNPs (single-nucleotide polymorphisms), indels (insertions and deletions), MNPs (multi-nucleotide polymorphisms), and complex events (composite insertion and substitution events) smaller than the length of a short-read sequencing alignment.

Please cite: Erik Garrison and Gabor Marth: Haplotype-based variant detection from short-read sequencing. (eprint) arXiv (2012)
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Freecontact
fast protein contact predictor
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FreeContact is a protein residue contact predictor optimized for speed. Its input is a multiple sequence alignment. FreeContact can function as an accelerated drop-in for the published contact predictors EVfold-mfDCA of DS. Marks (2011) and PSICOV of D. Jones (2011).

FreeContact is accelerated by a combination of vector instructions, multiple threads, and faster implementation of key parts. Depending on the alignment, 8-fold or higher speedups are possible.

A sufficiently large alignment is required for meaningful results. As a minimum, an alignment with an effective (after-weighting) sequence count bigger than the length of the query sequence should be used. Alignments with tens of thousands of (effective) sequences are considered good input.

jackhmmer(1) from the hmmer package, or hhblits(1) from hhsuite can be used to generate the alignments, for example.

This package contains the command line tool freecontact(1).

Please cite: László Kaján, Thomas A. Hopf, Matúš Kalaš, Debora S. Marks and Burkhard Rost: FreeContact: fast and free software for protein contact prediction from residue co-evolution. BMC Bioinformatics (2014)
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Fsa
Fast Statistical Alignment of protein, RNA or DNA sequences
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FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz.

FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:

  • FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.
  • FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.
  • FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.
  • The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned
Please cite: Robert K. Bradley, Adam Roberts, Michael Smoot, Sudeep Juvekar, Jaeyoung Do, Colin Dewey, Ian Holmes and Lior Pachter: Fast Statistical Alignment. (PubMed,eprint) PLoS Comput Biol. 5(5):e1000392 (2009)
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Remark of Debian Med team: Precondition for T-Coffee

see http://wiki.debian.org/DebianMed/TCoffee

Upstream address bounced when contacting about segfaults so it seems to be dead upstream and no good code quality.

Fsm-lite
frequency-based string mining (lite)
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A singe-core implementation of frequency-based substring mining used in bioinformatics to extract substrings that discriminate two (or more) datasets inside high-throughput sequencing data.

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Gamgi
General Atomistic Modelling Graphic Interface (GAMGI)
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General Atomistic Modelling Graphic Interface (GAMGI) bietet eine grafische Oberfläche, um atomare Strukturen zu erstellen, zu betrachten und zu analysieren. Das Programm ist für die Wissenschaftsgemeinschaft gedacht und bietet eine grafische Oberfläche an, um atomare Strukturen zu betrachten und Bilder für Präsentationen zu erstellen. Außerdem hilft es beim Lehren der atomaren Struktur der Materie.

The package is enhanced by the following packages: gamgi-data gamgi-doc
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Garli
phylogenetic analysis of molecular sequence data using maximum-likelihood
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GARLI, Genetic Algorithm for Rapid Likelihood Inference is a program for inferring phylogenetic trees. Using an approach similar to a classical genetic algorithm, it rapidly searches the space of evolutionary trees and model parameters to find the solution maximizing the likelihood score. It implements nucleotide, amino acid and codon-based models of sequence evolution, and runs on all platforms. The latest version adds support for partitioned models and morphology-like datatypes.

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Garlic
visualization program for biomolecules
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Garlic is written for the investigation of membrane proteins. It may be used to visualize other proteins, as well as some geometric objects. This version of garlic recognizes PDB format version 2.1. Garlic may also be used to analyze protein sequences.

It only depends on the X libraries, no other libraries are needed.

Features include:

  • The slab position and thickness are visible in a small window.
  • Atomic bonds as well as atoms are treated as independent drawable objects.
  • The atomic and bond colors depend on position. Five mapping modes are available (as for slab).
  • Capable to display stereo image.
  • Capable to display other geometric objects, like membrane.
  • Atomic information is available for atom covered by the mouse pointer. No click required, just move the mouse pointer over the structure!
  • Capable to load more than one structure.
  • Capable to draw Ramachandran plot, helical wheel, Venn diagram, averaged hydrophobicity and hydrophobic moment plot.
  • The command prompt is available at the bottom of the main window. It is able to display one error message and one command string.
Please cite: Damir Zucic and Davor Juretic: Precise Annotation of Transmembrane Segments with Garlic - a Free Molecular Visualization Program (eprint) Croatica Chemica Acta 77(1-2):397-401 (2004)
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Gasic
genome abundance similarity correction
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One goal of sequencing based metagenomic analysis is the quantitative taxonomic assessment of microbial community compositions. However, the majority of approaches either quantify at low resolution (e.g. at phylum level) or have severe problems discerning highly similar species. Yet, accurate quantification on species level is desirable in applications such as metagenomic diagnostics or community comparison. GASiC is a method to correct read alignment results for the ambiguities imposed by similarities of genomes. It has superior performance over existing methods.

Please cite: Martin S. Lindner and Bernhard Y. Renard: Metagenomic abundance estimation and diagnostic testing on species level. (PubMed,eprint) Nucleic Acids Research 41(1):e10 (2013)
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Gatb-core
Genome Analysis Toolbox with de-Bruijn graph
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The GATB-CORE project provides a set of highly efficient algorithms to analyse NGS data sets. These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (e.g. metagenomes). Read more about GATB at https://gatb.inria.fr/. By itself GATB-CORE is not an NGS data analysis tool. However, it can be used to create such tools. There already exist a set of ready-to-use tools relying on GATB-CORE library: see https://gatb.inria.fr/software/

Please cite: Erwan Drezen, Guillaume Rizk, Rayan Chikhi, Charles Deltel, Claire Lemaitre, Pierre Peterlongo and Dominique Lavenier: GATB: Genome Assembly & Analysis Tool Box. (eprint) Bioinformatics 30(20):2959-2961 (2014)
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Gbrowse
GMODs Generic Genome Browser
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Generic Genome Browser ist ein einfacher aber stark konfigurierbarer webbasierter Genombrowser. Er ist eine Komponente des Projekts Generic Model Organism Systems Database (GMOD). Einige der Merkmale:

  • simultane Vogelperspektive und detaillierte Ansicht des Genoms;
  • scrollen, zoomen, zentrieren;
  • beliebige URLs zu jeder Annotation anhängen;
  • anpassbare Reihenfolge und Aussehen der »Tracks« durch Administrator und Benutzer;
  • Suchen nach ID, Name oder Kommentar der Annotation;
  • unterstützt Annotationen Dritter über das Format GFF;
  • beibehalten der Einstellungen über Sitzungen hinaus;
  • DNA- und GFF-Exporte;
  • Verbindung zu verschiedenen Datenbanken, inklusive BioSQL und Chado;
  • unterstützt mehrere Sprachen;
  • laden von Merkmalen aus Erweiterungen;
  • anpassbare Erweiterungsarchitektur (z.B. BLAST laufen lassen, viele Formate exportieren und importieren, Oligonukleotide finden, Primer erstellen, Restriktionskarten erstellen, Merkmale bearbeiten).
The package is enhanced by the following packages: libbio-samtools-perl
Please cite: Maureen J. Donlin: Using the Generic Genome Browser (GBrowse). (eprint) Department of Biochemistry and Molecular Biology and Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine (2009)
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Gdpc
Visualisiert Molekulardynamik-Simulationen
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gpdc ist ein grafisches Programm zur Visualisierung von Ausgabedaten aus Molekulardynamik-Simulationen. Es verwendet sowohl das Standarddateiformat xyz als auch andere gebräuchliche Formate als Eingabe. Bilder jedes Frames können im JPG- oder im PNG-Format ausgegeben werden.

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Gemma
Genome-wide Efficient Mixed Model Association
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GEMMA is the software implementing the Genome-wide Efficient Mixed Model Association algorithm for a standard linear mixed model and some of its close relatives for genome-wide association studies (GWAS):

  • It fits a univariate linear mixed model (LMM) for marker association tests with a single phenotype to account for population stratification and sample structure, and for estimating the proportion of variance in phenotypes explained (PVE) by typed genotypes (i.e. "chip heritability").
  • It fits a multivariate linear mixed model (mvLMM) for testing marker associations with multiple phenotypes simultaneously while controlling for population stratification, and for estimating genetic correlations among complex phenotypes.
  • It fits a Bayesian sparse linear mixed model (BSLMM) using Markov chain Monte Carlo (MCMC) for estimating PVE by typed genotypes, predicting phenotypes, and identifying associated markers by jointly modeling all markers while controlling for population structure.
  • It estimates variance component/chip heritability, and partitions it by different SNP functional categories. In particular, it uses HE regression or REML AI algorithm to estimate variance components when individual-level data are available. It uses MQS to estimate variance components when only summary statisics are available.

GEMMA is computationally efficient for large scale GWAS and uses freely available open-source numerical libraries.

Please cite: Xiang Zhou and Matthew Stephens: Genome-wide efficient mixed-model analysis for association studies Nature Genetics 44:821–824 (2012)
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Genometester
toolkit for performing set operations on k-mer lists
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Toolkit for performing set operations - union, intersection and complement - on k-mer lists.

GenomeTester4 toolkit, which contains a novel tool GListCompare for performing union, intersection and complement (difference) set operations on k-mer lists. It contains examples of how these general operations can be combined to solve a variety of biological analysis tasks.

Please cite: Lauris Kaplinski, Maarja Lepamets and Maido Remm: GenomeTester4: a toolkit for performing basic set operations - union, intersection and complement on k-mer lists. (PubMed,eprint) GigaScience 4(1):58 (2015)
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Genometools
Vielseitiger Werkzeugsatz für Genomanalysen
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GenomeTools enthält eine nützliche Werkzeugsammlung für biologische Sequenzanalysen und -darstellungen in einem einzigen Binärprogramm.

Der Werkzeugsatz beinhaltet Binärprogramme für die Bearbeitung von Sequenzen und Annotationen, Sequenzkomprimierung, Erstellung von und Zugriff auf Indexstrukturen, Darstellung von Annotationen und vieles mehr.

Please cite: Gordon Gremme, Sascha Steinbiss and Stefan Kurtz: GenomeTools: a comprehensive software library for efficient processing of structured genome annotations.. (PubMed) IEEE/ACM Transactions on Computational Biology and Bioinformatics 10(3):645-656 (2013)
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Gentle
Suite zur Planung von genetischem Klonen
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GENtle ist eine Software zur Bearbeitung von DNA und Aminosäuren, Datenbankverwaltung, Plasmidkarten, Restriktion und Ligation, Alignments, Import der Daten von Sequenzierautomaten, Anzeigen von Gelbildern, PCS und vieles mehr.

Please cite: Magnus Manske: GENtle, a free multi-purpose molecular biology tool. (eprint) (2006)
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Gff2aplot
pair-wise alignment-plots for genomic sequences in PostScript
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A program to visualize the alignment of two genomic sequences together with their annotations. From GFF-format input files it produces PostScript figures for that alignment. The following menu lists many features of gff2aplot:

  • Comprehensive alignment plots for any GFF-feature. Attributes are defined separately so you can modify only whatsoever attributes for a given file or share same customization across different data-sets.
  • All parameters are set by default within the program, but it can be also fully configured via gff2ps-like flexible customization files. Program can handle several of such files, summarizing all the settings before producing the corresponding figure. Moreover, all customization parameters can be set via command-line switches, which allows users to play with those parameters before adding any to a customization file.
  • Source order is taken from input files, if you swap file order you can visualize alignment and its annotation with the new input arrangement.
  • All alignment scores can be visualized in a PiP box below gff2aplot area, using grey-color scale, user-defined color scale or score-dependent gradients.
  • Scalable fonts, which can also be chosen among the basic PostScript default fonts. Feature and group labels can be rotated to improve readability in both annotation axes.
  • The program is still defined as a Unix filter so it can handle data from files, redirections and pipes, writing output to standard-output and warnings to standard error.
  • gff2aplot is able to manage many physical page formats (from A0 to A10, and more -see available page sizes in its manual-), including user-defined ones. This allows, for instance, the generation of poster size genomic maps, or the use of a continuous-paper supporting plotting device, either in portrait or landscape.
  • You can draw different alignments on same alignment plot and distinguish them by using different colors for each.
  • Shape dictionary has been expanded, so that further feature shapes are now available (see manual).
  • Annotation projections through alignment plots (so called ribbons) emulate transparencies via complementary color fill patterns. This feature allows one to show color pseudo-blending when horizontal and vertical ribbons overlap.
Please cite: J. F. Abril, R. Guigó and T. Wiehe: gff2aplot: Plotting sequence comparisons. (PubMed,eprint) Bioinformatics 19(18):2477-2479 (2003)
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Gff2ps
Erstellt PostScript-Grafiken aus GFF-Dateien
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gff2ps ist ein Skript zur Umwandlung von GFF-formatierten Datensätzen in qualitativ hochwertige eindimensionale PostScript-Plots. Diese Plots können verwendet werden, um Genomstrukturen zu vergleichen und die Ausgaben von Programmen zur Annotation von Genomen zu visualisieren. gff2ps kann sehr einfach verwendet werden, weil es davon ausgeht, dass die GFF-Datei bereits genügend Formatierungsinformationen enthält. Die Ausgabe kann aber ebenso über zusätzliche Optionen und/oder eine Konfigurationsdatei den Wünschen entsprechend angepasst werden.

Please cite: J. F. Abril and R. Guigó: gff2ps: visualizing genomic annotations.. (PubMed,eprint) Bioinformatics 16(8):743-744 (2000)
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Ghemical
GNOME-Umgebung für molekulare Modellierung
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Ghemical ist ein Paket für die rechnergestützte Chemie, das in C++ geschrieben wurde. Es hat eine grafische Benutzeroberfläche und es unterstützt sowohl quantenmechanische (semi-empirische) als auch molekularmechanische Modelle. Zurzeit bietet es geometrische Optimierungen, molekulare Dynamik und eine große Menge an Visualisierungswerkzeugen, die OpenGL benutzen.

Ghemical benötigt externen Code, um quantenmechanische Berechnungen durchführen zu können. Semi-empirische Funktionen MNDO, MINDO/3, AM1 und PM3 werden vom MOPAC7-Paket (Public Domain) erbracht und sind in diesem Paket enthalten. Das MPQC-Paket wird verwendet, um ab-initio-Methoden zur Verfügung zu stellen. Die Methoden, die auf der Hartree-Fock-Theorie basieren, werden im Moment mit Basissätzen von STO-3G bis 6-31G** unterstützt.

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Giira
RNA-Seq driven gene finding incorporating ambiguous reads
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GIIRA is a gene prediction method that identifies potential coding regions exclusively based on the mapping of reads from an RNA-Seq experiment. It was foremost designed for prokaryotic gene prediction and is able to resolve genes within the expressed region of an operon. However, it is also applicable to eukaryotes and predicts exon intron structures as well as alternative isoforms.

Please cite: Franziska Zickmann, Martin S. Lindner and Bernhard Y. Renard: GIIRA—RNA-Seq driven gene finding incorporating ambiguous reads. (PubMed,eprint) Bioinformatics (2013)
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Glam2
Unterbrochene Protein-Motive aus ungeordneten Sequenzen
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GLAM2 ist ein Softwarepaket für das Finden von Motiven in Sequenzen, meist Aminosäuren- oder Nukleotidsequenzen. Ein Motiv ist ein wiederkehrendes Sequenzmuster: typische Beispiele sind die TATA-Box und das CAAX-Prenylierungs-Motiv. Die wichtigste Neuerung von GLAM2 ist, dass es das Einfügen und Löschen in Motiven erlaubt.

Dieses Paket enthält Programme für das Auffinden von Motiven durch einen Satz von gemeinsamen Sequenzen und den Abgleich dieser Motive mit einer Sequenzdatenbank, ebenso wie Dienste für die Konvertierung von glam2-Motiven in übliche Alignment-Formate, die Ausblendung von glam2-Motiven aus Sequenzen zur Auffindung schwächerer Motive und das Entfernen stark ähnlicher Elemente aus einem Satz von Sequenzen.

Das Paket enthält folgende Programme:

  glam2:       Auffinden von Motiven durch einen Satz von gemeinsamen
               Sequenzen;
  glam2scan:   Abgleich dieser Motive mit einer Sequenzdatenbank;
  glam2format: Konvertierung von glam2-Motiven in übliche
               Alignment-Formate;
  glam2mask:   Ausblendung von glam2-Motiven aus Sequenzen zur Auffindung
               schwächerer Motive;
  glam2-purge: Entfernen stark ähnlicher Elemente aus einem Satz von
               Sequenzen.

In diesem Binärpaket wurde die schnelle Fourier-Transformation (FFT-Fast Fourier Transformation) für das Programm glam2 integriert.

Please cite: Martin C. Frith, Neil F. W. Saunders, Bostjan Kobe and Timothy L. Bailey: Discovering Sequence Motifs with Arbitrary Insertions and Deletions. (PubMed) PLoS Computational Biology 4(5):e1000071 (2008)
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Grabix
wee tool for random access into BGZF files
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In biomedical research it is increasing practice to study the genetic basis of disease. This now frequently comprises the sequencing of human sequences. The output of the machine however is redundant, and the real sequence is the best sequence to explain the redundancy. The exchange of data happens only with compressed files - to huge and redundant to perform otherwise. One should avoid uncompression whenever possible.

grabix leverages the fantastic BGZF library of the samtools package to provide random access into text files that have been compressed with bgzip. grabix creates it's own index (.gbi) of the bgzipped file. Once indexed, one can extract arbitrary lines from the file with the grab command. Or choose random lines with the, well, random command.

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Graphlan
circular representations of taxonomic and phylogenetic trees
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GraPhlAn is a software tool for producing high-quality circular representations of taxonomic and phylogenetic trees. It focuses on concise, integrative, informative, and publication-ready representations of phylogenetically- and taxonomically-driven investigation.

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Grinder
Vielseitige Simulation von -omik-Shotgun und -Amplikonsquenzierungen
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Das vielseitige Programm Grinder erstellt zufällige Bibliotheken aus Shotgun- und Amplikonsequenzen, die auf DNA-, RNA- oder Protein-Referenzsequenzen aus einer FASTA-Datei basieren.

Grinder kann Shotgun- und Amplikon-Datensätze der Genomik, Metagenomik, Transkriptomik, Metatranskriptomik, Proteomik und Metaproteomik aus aktuellen Sequenziertechniken wie Sanger, 454, Illumina erstellen. Diese simulierten Datensätze können die Genauigkeit von bioinformatischen Werkzeugen unter spezifischen Hypothesen testen, z.B. mit oder ohne Sequenzierfehler oder mit niedriger oder hoher Diversität. Grinder kann außerdem bei der Auswahl der Sequenziermethode für ein sequenzbasiertes Projekt helfen, etwa wie viele kurze Sequenzen sequenziert werden sollen und ob es eine Paired-End-Bibliothek sein soll oder nicht.

Please cite: Florent E. Angly, Dana Willner, Forest Rohwer, Philip Hugenholtz and Gene W. Tyson: Grinder: a versatile amplicon and shotgun sequence simulator. (PubMed,eprint) Nucleic Acids Research Epub ahead of print (2012)
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Gromacs
Simulator für Moleküldynamik, Werkzeuge für das Erstellen der Modelle und deren Analyse
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GROMACS ist ein vielseitiges Paket, um Molekulardynamik anzuwenden, z.B. um die Newtonschen Bewegungsgleichungen für Systeme mit Hunderten bis zu Millionen von Teilchen zu simulieren.

Es wurde primär für biochemische Moleküle wie Proteine und Fette entworfen, die eine Vielzahl von komplizierten Wechselwirkungen zwischen Bindungen aufweisen. Da aber GROMACS die zwischenmolekularen Interaktionen (welche in Simulationen dominieren) extrem schnell berechnen kann, nutzen es viele Gruppen auch für Forschungen an nicht-biologischen Systemen, z.B. an Polymeren.

Please cite: Berk Hess, Carsten Kutzner, David van der Spoel and Erik Lindahl: GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. (eprint) J. Chem. Theory Comput. 4(3):435-447 (2008)
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Gubbins
phylogenetic analysis of genome sequences
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Gubbins supports rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences.

Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively identifies loci containing elevated densities of base substitutions while concurrently constructing a phylogeny based on the putative point mutations outside of these regions. Simulations demonstrate the algorithm generates highly accurate reconstructions under realistic models of short-term bacterial evolution, and can be run in only a few hours on alignments of hundreds of bacterial genome sequences.

Please cite: Nicholas J. Croucher, Andrew J. Page, Thomas R. Connor, Aidan J. Delaney, Jacqueline A. Keane, Stephen D. Bentley, Julian Parkhill and Simon R. Harris: Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. (PubMed,eprint) Nucleic Acids Research 43(3):e15 (2014)
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Gwama
Metaanalysen für genomweite Assoziationen
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Die Software GWAMA (Genome-Wide Association Meta Analysis) führt Metaanalysen der Resultate von genomweiten Assoziationsstudien (GWAS) binärer oder quantitativer Phänotypen durch. Fixed- und Random-Effect-Metaanalysen werden sowohl für direkt genotypisierte als auch zugerechnete SNPs durchgeführt. Dabei werden Schätzungen des Verhältnisses der Allel-Wahrscheinlichkeiten und ein 95%-Konfidenzintervall für binäre Eigenschaften sowie Schätzungen der Größe von Allel-Effekten und Standardfehlern für quantitative Phänotypen verwendet. GWAMA kann für die Analyse von Resultaten aller unterschiedlichen genetischen Modelle (multiplikativ, additiv, dominant, rezessiv) verwendet werden. Die Software beinhaltet Möglichkeiten zur Ausnahmebehandlung, um Fehler in der Strangausrichtung und »allele flipping« zu entdecken, sowie um Tests zur Heterogenität von Effekten zwischen Studien durchzuführen.

Please cite: Reedik Mägi and Andrew P. Morris: GWAMA: software for genome-wide association meta-analysis. (eprint) BMC Bioinformatics 11(May):288 (2010)
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Harvest-tools
archiving and postprocessing for reference-compressed genomic multi-alignments
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HarvestTools is a utility for creating and interfacing with Gingr files, which are efficient archives that the Harvest Suite uses to store reference-compressed multi-alignments, phylogenetic trees, filtered variants and annotations. Though designed for use with Parsnp and Gingr, HarvestTools can also be used for generic conversion between standard bioinformatics file formats.

Please cite: Todd J. Treangen, Brian D. Ondov, Sergey Koren and Adam M. Phillippy: Rapid Core-Genome Alignment and Visualization for Thousands of Intraspecific Microbial Genomes. (PubMed,eprint) bioRxiv 15(11):524 (2014)
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Hhsuite
Sensible Proteinsequenzsuchen, basierend auf HMM-HMM-Alignment
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HH-suite ist ein quelloffenes Softwarepaket für sensible Proteinsequenzsuchen, basierend auf paarweisen Alignments von Hidden-Markov-Modellen (HMMe).

Dieses Paket enthält HHsearch, HHblits sowie weitere Programme und Hilfswerkzeuge.

HHsearch akzeptiert als Eingabe ein multiples Sequenzalignment (MSA) oder Profil-HMM und durchsucht eine HMM-Datenbank (z.B. PDB, Pfam oder InterPRo) nach homologen Proteinen. HHsearch wird oft bei Proteinstrukturvorhersagen verwendet, um homologe Matrizen (Templates) zu erkennen und hochakkurate paarweise Alignments mit Abfrage-Matrizen für Homology Modelling zu erstellen.

HHblits kann hochqualitative MSAs aus einzelnen Sequenzen oder aus MSAs erstellen. Es transformiert diese in ein Abfrage-HMM und fügt der aktualisierten Abfrage-HMM - mittels iterativer Suche - signifikant ähnliche Sequenzen der vorherigen Suche hinzu, um diese bei der nächsten Suchiteration zu verwenden. HHblits ist verglichen mit PSI-BLAST schneller, bis zu doppelt so sensibel und erstellt genauere Alignments.

Please cite: Michael Remmert, Andreas Biegert, Andreas Hauser and Johannes Söding: HHblits: Lightning-fast iterative protein sequence searching by HMM-HMM alignment.. (PubMed) Nat. Methods 9(2):173-175 (2011)
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Hilive
realtime alignment of Illumina reads
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HiLive is a read mapping tool that maps Illumina HiSeq (or comparable) reads to a reference genome right in the moment when they are produced. This means, read mapping is finished as soon as the sequencer is finished generating the data.

Please cite: Martin S. Lindner, Benjamin Strauch, Jakob M. Schulze, Simon H. Tausch, Piotr W. Dabrowski, Andreas Nitsche and Bernhard Y. Renard: HiLive: real-time mapping of illumina reads while sequencing. (PubMed) Bioinformatics 33(6):917-919 (2017)
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Hinge
long read genome assembler based on hinging
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HINGE is a genome assembler that seeks to achieve optimal repeat resolution by distinguishing repeats that can be resolved given the data from those that cannot. This is accomplished by adding “hinges” to reads for constructing an overlap graph where only unresolvable repeats are merged. As a result, HINGE combines the error resilience of overlap-based assemblers with repeat-resolution capabilities of de Bruijn graph assemblers.

Please cite: Govinda M Kamath, Ilan Shomorony, Fei Xia, Thomas Courtade and David N Tse: HINGE: Long-read assembly achieves optimal repeat resolution. (PubMed,eprint) Genome Research (2017)
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Hisat2
graph-based alignment of short nucleotide reads to many genomes
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HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as against a single reference genome). Based on an extension of BWT for graphs a graph FM index (GFM) was designed and implementd. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).

Please cite: Daehwan Kim, Ben Langmead and Steven L Salzberg: HISAT: a fast spliced aligner with low memory requirements. Nature Methods 12(4):357-360 (2015)
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Hmmer
Profil-Hidden-Markov-Modelle für Protein-Sequenzanalyse
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HMMER ist eine Implementierung der Profile-Hidden-Markov-Modelle für eine sensitive Suche in biologischen Sequenzdatenbanken mit multiplen Sequenzalignments als Anfragen.

Mit einem multiplen Sequenzalignment als Eingabe baut HMMER ein statistisches Modell, genannt »Hidden-Markov-Modell«. Mit diesem kann in Sequenzdatenbanken nach homologen Sequenzen gesucht werden. Dabei können gleichzeitig, der gesuchten Proteinfamilie zugehörige, Sequenzen alignt werden.

Please cite: S. R. Eddy: Profile hidden Markov models. (PubMed,eprint) Bioinformatics 14(9):755-763 (1998)
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Hmmer2
Profil-Hidden-Markov-Modelle für Protein-Sequenzanalyse
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HMMER ist eine Implementierung der Profile-Hidden-Markov-Modelle für eine sensitive Suche in biologischen Sequenzdatenbanken mit multiplen Sequenzalignments als Anfragen.

Mit einem multiplen Sequenzalignment als Eingabe baut HMMER ein statistisches Modell, genannt »Hidden-Markov-Modell«. Mit diesem kann in Sequenzdatenbanken nach homologen Sequenzen gesucht werden. Dabei können gleichzeitig, der gesuchten Proteinfamilie zugehörige, Sequenzen alignt werden.

Please cite: Eddy, Sean R.: Profile hidden Markov models. (PubMed) Bioinformatics 14(9):755-763 (1998)
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Remark of Debian Med team: This older version of HMMER is used in some applications

While Debian has HMMER 3 since some time there are users of HMMER 2 interested in having this old version available and thus the package is reintroduced.

Hyphy-mpi
Hypothesis testing using Phylogenies (MPI version)
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HyPhy is an open-source software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and machine learning. It features a complete graphical user interface (GUI) and a rich scripting language for limitless customization of analyses. Additionally, HyPhy features support for parallel computing environments (via message passing interface) and it can be compiled as a shared library and called from other programming environments such as Python or R. Continued development of HyPhy is currently supported in part by an NIGMS R01 award 1R01GM093939.

This package provides an executable using MPI to do multiprocessing.

Please cite: Sergei L. Kosakovsky Pond, Simon D. W. Frost and Spencer V. Muse: HyPhy: hypothesis testing using phylogenies. (PubMed,eprint) Bioinformatics 21(5):676-679 (2005)
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Hyphy-pt
Hypothesentest unter Verwendung von Phylogenie (pthreads Version)
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HyPhy ist ein quelloffenes Softwarepaket für die Analyse genetischer Sequenzen unter Verwendung phylogenetischer Techniken, molekularer Evolution und maschinellem Lernen. Es beinhaltet eine komplette grafische Benutzeroberfläche (GUI) und eine mächtige Skriptsprache für grenzenlose Anpassungsmöglichkeiten der Analysen. Zusätzlich unterstützt HyPhy Umgebungen für parallele Datenverarbeitung (via einer Schnittstelle für den Nachrichtenaustausch) und kann als Laufzeitbibliothek kompiliert und von anderen Programmierumgebungen, wie Python oder R, aufgerufen werden. Die Weiterentwicklung von HyPhy wird momentan teilweise von einem Forschungsprojekt-Zuschuss der NIGMS (1R01GM093939) unterstützt.

Dieses Paket enthält eine Ausführung mit pthreads für Simultanverarbeitung.

Please cite: Sergei L. Kosakovsky Pond, Simon D. W. Frost and Spencer V. Muse: HyPhy: hypothesis testing using phylogenies. (PubMed,eprint) Bioinformatics 21(5):676-679 (2005)
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Idba
iterative De Bruijn Graph short read assemblers
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IDBA stands for iterative de Bruijn graph assembler. In computational sequence biology, an assembler solves the puzzle coming from large sequencing machines that feature many gigabytes of short reads from a large genome.

This package provides several flavours of the IDBA assembler, as they all share the same source tree but serve different purposes and evolved over time.

IDBA is the basic iterative de Bruijn graph assembler for second-generation sequencing reads. IDBA-UD, an extension of IDBA, is designed to utilize paired-end reads to assemble low-depth regions and use progressive depth on contigs to reduce errors in high-depth regions. It is a generic purpose assembler and especially good for single-cell and metagenomic sequencing data. IDBA-Hybrid is another update version of IDBA-UD, which can make use of a similar reference genome to improve assembly result. IDBA-Tran is an iterative de Bruijn graph assembler for RNA-Seq data.

Please cite: Yu Peng, Henry C. M. Leung, S. M. Yiu and Francis Y. L. Chin: IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. (PubMed,eprint) Bioinformatics 28(11):1420-1428 (2012)
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Indelible
powerful and flexible simulator of biological evolution
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INDELible is a new, portable, and flexible application for biological sequence simulation that combines many features in the same place for the first time. Using a length-dependent model of indel formation it can simulate evolution of multi-partitioned nucleotide, amino-acid, or codon data sets through the processes of insertion, deletion, and substitution in continuous time.

Nucleotide simulations may use the general unrestricted model or the general time reversible model and its derivatives, and amino-acid simulations can be conducted using fifteen different empirical rate matrices. Substitution rate heterogeneity can be modeled via the continuous and discrete gamma distributions, with or without a proportion of invariant sites. INDELible can also simulate under non-homogeneous and non-stationary conditions where evolutionary models are permitted to change across a phylogeny.

Unique among indel simulation programs, INDELible offers the ability to simulate using codon models that exhibit nonsynonymous/synonymous rate ratio heterogeneity among sites and/or lineages.

Please cite: William Fletcher and Ziheng Yang: INDELible: A Flexible Simulator of Biological Sequence Evolution. (eprint) Molecular Biology and Evolution 26(8):1879-1888 (2009)
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Infernal
Rückschluss auf Alignments der RNA-Sekundärstruktur
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Infernal ("INFERence of RNA ALignment") durchsucht DNA-Sequenzdatenbanken nach RNA-Struktur- und Sequenzähnlichkeiten. Es stellt eine Implementierung eines Spezialfalls der stochastisch kontextfreien Grammatiken, den sogenannten Kovarianzmodellen (CMs), bereit. Ein CM ist wie ein Sequenzprofil, bewertet jedoch eine Kombination aus Sequenzübereinstimmung und Übereinstimmung sekundärer RNA-Strukturen. Daher kann ein CM in vielen Fällen eher RNA- Homologe erkennen, deren Sekundärstruktur besser konserviert ist als deren primäre Sequenz.

Dieses Werkzeug ist eine integrale Komponente der Datenbank Rfam.

Please cite: Eric P. Nawrocki, Diana L. Kolbe and Sean R. Eddy: Infernal 1.0: inference of RNA alignments. (PubMed,eprint) Bioinformatics 25(10):1335-1337 (2009)
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Ipig
integrating PSMs into genome browser visualisations
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iPiG targets the integration of peptide spectrum matches (PSMs) from mass spectrometry (MS) peptide identifications into genomic visualisations provided by genome browser such as the UCSC genome browser (http://genome.ucsc.edu/).

iPiG takes PSMs from the MS standard format mzIdentML (*.mzid) or in text format and provides results in genome track formats (BED and GFF3 files), which can be easily imported into genome browsers.

Please cite: Mathias Kuhring and Bernhard Y. Renard: iPiG: Integrating Peptide Spectrum Matches into Genome Browser Visualizations. (PubMed,eprint) PLoS ONE 7(12):e50246 (2012)
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Iqtree
efficient phylogenetic software by maximum likelihood
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IQ-TREE is a very efficient maximum likelihood phylogenetic software with following key features among others:

  • A novel fast and effective stochastic algorithm to estimate maximum likelihood trees. IQ-TREE outperforms both RAxML and PhyML in terms of likelihood while requiring similar amount of computing time (see Nguyen et al., 2015)
  • An ultrafast bootstrap approximation to assess branch supports (see Minh et al., 2013).
  • A wide range of substitution models for binary, DNA, protein, codon, and morphological alignments.
  • Ultrafast model selection for all data types, 10 to 100 times faster than jModelTest and ProtTest.
  • Finding best partition scheme like PartitionFinder.
  • Partitioned models with mixed data types for phylogenomic (multi- gene) alignments, allowing for separate, proportional, or joint branch lengths among genes.
  • Supporting the phylogenetic likelihod library (PLL) (see Flouri et al., 2014)
Please cite: Lam Tung Nguyen, Heiko A. Schmidt, Arndt von Haeseler and Bui Quang Minh: IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies. (PubMed,eprint) Mol. Biol. Evol. 32(1):268-274 (2015)
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Iva
iterative virus sequence assembler
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IVA is a de novo assembler designed to assemble virus genomes that have no repeat sequences, using Illumina read pairs sequenced from mixed populations at extremely high depth.

IVA's main algorithm works by iteratively extending contigs using aligned read pairs. Its input can be just read pairs, or additionally you can provide an existing set of contigs to be extended. Alternatively, it can take reads together with a reference sequence.

Please cite: M. Hunt, A. Gall, S. H. Ong, J. Brener, B. Ferns, P. Goulder, E. Nastouli, J. A. Keane, P. Kellam and T. D. Otto: IVA: accurate de novo assembly of RNA virus genomes. (PubMed) Bioinformatics 31(14):2374-2376 (2015)
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Jaligner
Smith-Waterman algorithm with Gotoh's improvement
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JAligner is an open source Java implementation of the Smith-Waterman algorithm with Gotoh's improvement for biological local pairwise sequence alignment with the affine gap penalty model.

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Jalview
Editor für multiple Alignments
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JalView ist ein Java-Alignment-Editor. Er ist imstande sequenzielle Alignierung zu verarbeiten, welche durch Programme erstellt wurde die Alignierungsalgorithmen, wie z.B. clustalw, kalign und t-coffee, implementiert haben.

Er hat viele Fähigkeiten, wird aktiv entwickelt, ist im Vergleich zu BioEdit vorteilhafter, während er frei ist wie in Meinungsfreiheit.

Please cite: Andrew M. Waterhouse, James B. Procter, David M. A. Martin, Michèle Clamp and Geoffrey J. Barton: Jalview Version 2-a multiple sequence alignment editor and analysis workbench. (PubMed,eprint) Bioinformatics 25:1189-1191 (2009)
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Jellyfish
Zählt k-mere in DNA-Sequenzen
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JELLYFISH ist ein Werkzeug für schnelles, speichereffizientes Zählen von k-meren in DNA. Ein k-mer ist ein Substring der Länge k. Die Vorkommen aller solcher Substrings zu zählen ist ein zentraler Schritt in vielen Analysen von DNA-Sequenzen. JELLYFISH kann k-mere mit einer Größenordnung weniger Speicher und einer Größenordnung schneller als andere Pakete zählen. Dies ist durch eine effiziente Kodierung einer Hashtabelle und durch Ausnutzung der CPU-Anweisung »Compare-and-Swap« für eine erhöhte Parallelisierung möglich.

JELLYFISH ist ein Befehlszeilenprogramm, das FASTA- und multi-FASTA-Dateien bestehend aus DNA-Sequenzen liest. Die Zählung der k-mere wird in einem Binärformat ausgegeben, das mit dem Befehl »jellyfish dump« in ein menschenlesbares Textformat übersetzt werden kann.

Please cite: Guillaume Marcais and Carl Kingsford: A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27(6):764-770 (2011)
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Jmodeltest
HPC selection of models of nucleotide substitution
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jModelTest is a tool to carry out statistical selection of best-fit models of nucleotide substitution. It implements five different model selection strategies: hierarchical and dynamical likelihood ratio tests (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC), and a decision theory method (DT). It also provides estimates of model selection uncertainty, parameter importances and model-averaged parameter estimates, including model-averaged tree topologies. jModelTest 2 includes High Performance Computing (HPC) capabilities and additional features like new strategies for tree optimization, model- averaged phylogenetic trees (both topology and branch length), heuristic filtering and automatic logging of user activity.

Please cite: Diego Darriba, Guillermo L Taboada, Ramón Doallo and David Posada: jModelTest 2: more models, new heuristics and parallel computing. (PubMed) Nature Methods 9(8):772 (2012)
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Jmol
Programm zur Darstellung von Molekülen
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Jmol ist ein Java-Programm zur Darstellung von dreidimensionalen chemischen Strukturen auf Molekülebene. Es kann eine Vielzahl von Dateitypen und Ausgaben von Programmen der Quantenchemie lesen sowie Multiframe-Dateien und berechnete Normalmodi von Quantenprogrammen animieren. Es kann Chemikalien, Kristalle, Materialien und Biomoleküle anzeigen. Jmol kann für Studenten, Lehrende und Forscher in der Chemie und Biochemie nützlich sein.

Jmol kann unter anderem folgende Dateiformate lesen: PDB, XYZ, CIF, CML, MDL Molfile, Gaussian, GAMESS, MOPAC, ABINIT, ACES-II, Dalton und VASP.

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Kalign
Globales und fortschreitendes multiples Sequenzalignment
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Das Befehlszeilenwerkzeug Kalign gleicht mehrere biologische Sequenzen ab. Für die Erhöhung von Präzision und Geschwindigkeit nutzt es den Muth-Manber-Algorithmus, der in großen Datenmengen sich wiederholende Muster ermittelt. Das Programm verwendet einen globalen, fortschreitenden Alignment-Ansatz, ergänzt durch den Einsatz eines annähernden Musterabgleich-Algorithmus zur Berechnung von Sequenzabständen und durch die Einbeziehung lokaler Übereinstimmungen in ein ansonsten globales Alignment.

Please cite: Timo Lassmann, Oliver Frings and Erik L. L. Sonnhammer: Kalign2: high-performance multiple alignment of protein and nucleotide sequences allowing external features. (PubMed,eprint) Nucl. Acids Res. 37(3):858-865 (2009)
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Khmer
in-memory DNA sequence kmer counting, filtering & graph traversal
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khmer is a library and suite of command line tools for working with DNA sequence. It is primarily aimed at short-read sequencing data such as that produced by the Illumina platform. khmer takes a k-mer-centric approach to sequence analysis, hence the name.

Please cite: Michael R. Crusoe, Hussien F. Alameldin, Sherine Awad, Elmar Bucher, Adam Caldwell, Reed Cartwright, Amanda Charbonneau, Bede Constantinides, Greg Edvenson, Scott Fay, Jacob Fenton, Thomas Fenzl, Jordan Fish, Leonor Garcia-Gutierrez, Phillip Garland, Jonathan Gluck, Iván González, Sarah Guermond, Jiarong Guo, Aditi Gupta, Joshua R. Herr, Adina Howe, Alex Hyer, Andreas Härpfer, Luiz Irber, Rhys Kidd, David Lin, Justin Lippi, Tamer Mansour, Pamela McA'Nulty, Eric McDonald, Jessica Mizzi, Kevin D. Murray, Joshua R. Nahum, Kaben Nanlohy, Alexander Johan Nederbragt, Humberto Ortiz-Zuazaga, Jeramia Ory, Jason Pell, Charles Pepe-Ranney, Zachary N Russ, Erich Schwarz, Camille Scott, Josiah Seaman, Scott Sievert, Jared Simpson, Connor T. Skennerton, James Spencer, Ramakrishnan Srinivasan, Daniel Standage, James A. Stapleton, Joe Stein, Susan R Steinman, Benjamin Taylor, Will Trimble, Heather L. Wiencko, Michael Wright, Brian Wyss, Qingpeng Zhang, en zyme and C. Titus Brown: The khmer software package: enabling efficient sequence analysis. (2015)
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Kineticstools
detection of DNA modifications
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Tools for detecting DNA modifications from single molecule, real-time (SMRT®) sequencing data. This tool implements the P_ModificationDetection module in SMRT® Portal, used by the RS_Modification_Detection and RS_Modifications_and_Motif_Detection protocol. Researchers interested in understanding or extending the modification detection algorithms can use these tools as a starting point.

This package is part of the SMRTAnalysis suite.

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King-probe
Evaluate and visualize protein interatomic packing
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king-probe is a program that allows one to evaluate atomic packing, either within or between molecules. It generates "contact dots" where atoms are in close contact.

The program king-probe generates "contact dots" at points on the van der Waals surface of atoms which are in close proximity to other atoms; reading atomic coordinates in protein databank (PDB) format files and writing color-coded dot lists (spikes where atoms clash) for inclusion in a kinemage.

Please cite: J. Michael Word, Simon C. Lovell, Thomas H. LaBean, Hope C. Taylor, Michael E. Zalis, Brent K. Presley, Jane S. Richardson and David C. Richardson: Visualizing and Quantifying Molecular Goodness-of-Fit: Small-probe Contact Dots with Explicit Hydrogen Atoms. (PubMed,eprint) J. Mol. Biol. 285(4):1709-1731 (1999)
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Kissplice
Detection of various kinds of polymorphisms in RNA-seq data
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KisSplice is a piece of software that enables the analysis of RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows one to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.

Please cite: Gustavo AT Sacomoto, Janice Kielbassa, Rayan Chikhi, Raluca Uricaru, Pavlos Antoniou, Marie-France Sagot, Pierre Peterlongo and Vincent Lacroix: KISSPLICE: de-novo calling alternative splicing events from RNA-seq data. (PubMed,eprint) BMC Bioinformatics 13((Suppl 6)):S5 (2012)
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Kmc
count kmers in genomic sequences
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The kmc software is designed for counting k-mers (sequences of consecutive k symbols) in a set of reads. K-mer counting is important for many bioinformatics applications, e.g. developing de Bruijn graph assemblers.

Building de Bruijn graphs is a commonly used approach for genome assembly with data from second-generation sequencing. Unfortunately, sequencing errors (frequent in practice) result in huge memory requirements for de Bruijn graphs, as well as long build time. One of the popular approaches to handle this problem is filtering the input reads in such a way that unique k-mers (very likely obtained as a result of an error) are discarded.

Thus, KMC scans the raw reads and produces a compact representation of all non-unique reads accompanied with number of their occurrences. The algorithm implemented in KMC makes use mostly of disk space rather than RAM, which allows one to use KMC even on rather typical personal computers. When run on high-end servers (what is necessary for KMC competitors) it outperforms them in both memory requirements and speed of computation. The disk space necessary for computation is in order of the size of input data (usually it is smaller).

Please cite: S. Deorowicz, M. Kokot, Sz. Grabowski and A. Debudaj-Grabysz: KMC 2: Fast and resource-frugal k-mer counting. (PubMed) Bioinformatics 31(10):1569-1576 (2015)
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Kmer
Programmsuite für die DNA-Sequenzanalyse
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Das Paket kmer ist eine Werkzeugsuite für die DNA-Sequenzanalyse. Es liefert Werkzeuge zum Suchen (ESTs, mRNAs, Sequenzierungsabschnitte), zum Vergleichen (ESTs, mRNAs, ganze Genome) und eine Auswahl von Analysen basierend auf K-meren.

Dieses Metapaket ist abhängig von den ausführbaren Komponenten der kmer-Suite.

Please cite: B. Walenz and L. Florea: Sim4db and leaff: Utilities for fast batched spliced alignment and sequence indexing. (PubMed) Bioinformatics 27(13):1869-1870 (2011)
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Kraken
assigning taxonomic labels to short DNA sequences
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Kraken is a system for assigning taxonomic labels to short DNA sequences, usually obtained through metagenomic studies. Previous attempts by other bioinformatics software to accomplish this task have often used sequence alignment or machine learning techniques that were quite slow, leading to the development of less sensitive but much faster abundance estimation programs. Kraken aims to achieve high sensitivity and high speed by utilizing exact alignments of k-mers and a novel classification algorithm.

In its fastest mode of operation, for a simulated metagenome of 100 bp reads, Kraken processed over 4 million reads per minute on a single core, over 900 times faster than Megablast and over 11 times faster than the abundance estimation program MetaPhlAn. Kraken's accuracy is comparable with Megablast, with slightly lower sensitivity and very high precision.

The package is enhanced by the following packages: jellyfish1
Please cite: Derrick E Wood and Steven L Salzberg: Kraken: ultrafast metagenomic sequence classification using exact alignments. (PubMed,eprint) Genome Biol. 15(3):R46 (2014)
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Lamarc
Likelihood Analysis with Metropolis Algorithm using Random Coalescence
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LAMARC is a program which estimates population-genetic parameters such as population size, population growth rate, recombination rate, and migration rates. It approximates a summation over all possible genealogies that could explain the observed sample, which may be sequence, SNP, microsatellite, or electrophoretic data. LAMARC and its sister program Migrate are successor programs to the older programs Coalesce, Fluctuate, and Recombine, which are no longer being supported. The programs are memory-intensive but can run effectively on workstations.

Please cite: Mary K. Kuhner: Coalescent genealogy samplers: windows into population history. (PubMed) Trends in Ecology & Evolution 24(2):86-93 (2009)
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Remark of Debian Med team: This package ships with BioLinux http://envgen.nox.ac.uk/biolinux.html.

In 1/2018 upstream has apparently updated their tarball to help the redistribution of their software. Someone please go for it.

Lambda-align
Local Aligner for Massive Biological DatA
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Lambda is a local biosequence aligner optimized for many query sequences and searches in protein space. It is compatible to the de facto standard tool BLAST, but often outperforms the best currently available alternatives at reproducing BLAST’s results and is the fastest compared with the current state of the art at comparable levels of sensitivity.

Please cite: Hannes Hauswedell, Jochen Singer and Knut Reinert: Lambda: the local aligner for massive biological data. (PubMed,eprint) Bioinformatics 30(17):i349-i355 (2014)
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Last-align
Vergleich biologischer Sequenzen für Genome
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LAST ist eine Software für den Vergleich und die Alignierung von Sequenzen, in der Regel DNA- oder Protein-Sequenzen. LAST ähnelt BLAST, kommt jedoch besser mit sehr großen Mengen an Sequenzdaten zurecht. Hier sind zwei Dinge, die LAST gut beherrscht:

  • Vergleich großer Genome (z.B. von Säugetieren).
  • Kartierung viele Sequenz-Markierungen auf einem Genom.

Die wichtigste technische Neuerung ist, dass LAST erste Übereinstimmungen auf der Grundlage ihrer Vielfachheit findet, anstatt eine feste Größe zu verwenden (z.B. verwendet BLAST 10-mere). Dies ermöglicht es, Markierungen (Tags) ohne wiederholte Maskierung (repeat-masking) auf Genome anzuwenden, ohne durch wiederholte Treffer überschüttet zu werden. Um diese Übereinstimmungen variabler Größe zu finden, verwendet es ein von Vmatch inspiriertes Suffix-Array. Um eine hohe Empfindlichkeit zu erreichen, verwendet LAST ein nicht zusammenhängendes Suffix-Array, analog zu »spaced seeds«.

Please cite: Martin C. Frith, Raymond Wan and Paul Horton: Incorporating sequence quality data into alignment improves DNA read mapping. (PubMed,eprint) Nucl. Acids Res. 38(7):e100 (2010)
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Leaff
biological sequence library utilities and applications
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LEAFF (Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.

This package is part of the Kmer suite.

Please cite: B. Walenz and L. Florea: Sim4db and leaff: Utilities for fast batched spliced alignment and sequence indexing. (PubMed) Bioinformatics 27(13):1869-1870 (2011)
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Lefse
determine features of organisms, clades, taxonomic units, genes
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LEfSe (Linear discriminant analysis Effect Size) determines the features (organisms, clades, operational taxonomic units, genes, or functions) most likely to explain differences between classes by coupling standard tests for statistical significance with additional tests encoding biological consistency and effect relevance.

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Librg-utils-perl
Parser und Programme für Formatkonvertierungen, verwendet von (z.B.) profphd
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Dieses Paket trägt zum PredictProtein-Server für die automatisierte strukturelle Annotierung von Proteinsequenzen bei. Es stellt eine Reihe an Konvertierungswerkzeugen bereit wie:

  • blast2saf.pl
  • blastpgp_to_saf.pl
  • conv_hssp2saf.pl
  • copf.pl
  • hssp_filter.pl
  • safFilterRed.pl

Diese Werkzeuge werden von den folgenden Modulen unterstützt:

  • RG:Utils::Conv_hssp2saf
  • RG:Utils::Copf
  • RG:Utils::Hssp_filter
Libvcflib-tools
C++ library for parsing and manipulating VCF files (tools)
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The Variant Call Format (VCF) is a flat-file, tab-delimited textual format intended to concisely describe reference-indexed variations between individuals. VCF provides a common interchange format for the description of variation in individuals and populations of samples, and has become the defacto standard reporting format for a wide array of genomic variant detectors.

vcflib provides methods to manipulate and interpret sequence variation as it can be described by VCF. It is both:

  • an API for parsing and operating on records of genomic variation as it can be described by the VCF format,
  • and a collection of command-line utilities for executing complex manipulations on VCF files.

This package contains several tools using the library.

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Logol
Pattern matching tool using Logol language