Debian Med Project
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Summary
Cloud
클라우드 컴퓨팅에서 사용할 수 있는 Debian Med 생물정보학 어플리케이션

이 메타패키지는 그래픽 툴킷에 의존하지 않고 그래서 공간이 제한될 수 있는 클라우드 컴퓨팅 클러스터에서 사용 가능한 시스템 이미지에 알맞은 생명 과학용 분자 생물학, 구조 생물학 및 생물 정보학 관련 데비안 패키지를 설치할 것입니다.

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

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Debian Med Cloud packages

Official Debian packages with high relevance

abyss
짧은 읽기를 위한 de novo, 병렬, 시퀀스 어셈블러
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ABySS는 짧은 읽기를 위해 설계된 de novo, 병렬, 시퀀스 어셈블러입니다. 게놈 또는 전사체 시퀀스 데이타를 조립하는데 사용될 수 있습니다. 병렬화는 MPI, OpenMP, pthread를 사용해서 수행됩니다.

Please cite: Shaun D. Jackman, Benjamin P. Vandervalk, Hamid Mohamadi, Justin Chu, Sarah Yeo, S. Austin Hammond, Golnaz Jahesh, Hamza Khan, Lauren Coombe, Rene L. Warren and İnanç Birol: "ABySS 2.0: resource-efficient assembly of large genomes using a Bloom filter". (PubMed,eprint) Genome Research 27(5):768-777 (2017)
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Topics: Sequence assembly
acedb-other
retrieval of DNA or protein sequences
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This package collects all those smallish applications that acedb collects under its 'other' target of its Makefile.

efetch: presumably short for 'entry fetch' collects sequence information from common DNA and protein databases.

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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aevol
실리코에서 진화 실험을 실행하는 디지탈 유전학 모델
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Aevol은 디지탈 유전학 모델입니다: 디지탈 유기체의 개체군은 선택과 변이 과정을 거쳐 다윈의 역학을 만들어 냅니다.

선택 특성 (예, 모집단 크기, 환경 유형, 환경 변화) 또는 변동 (예, 돌연변이율, 염색체 재배열율, 재배열 유형, 수평 이동)을 수정함으로써 이러한 매개 변수가 진화된 유기체의 구조에 미치는 영향을 실험적으로 연구할 수 있습니다. 특히 Aevol은 정확하고 현실적인 게놈 모델을 통합하기 때문에 게놈의 구조적 변이 (예, 유전자 수, synteny, 코딩 서열 비율)를 연구 할 수 있습니다.

시뮬레이션 플랫폼은 계통 발생을 분석하고 진화에 따른 유기체 및 개체군의 여러 특성을 측정하기 위한 도구 세트와 함께 제공됩니다.

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)
alien-hunter
Interpolated Variable Order Motifs to identify horizontally acquired DNA
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Alien_hunter is an application for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs). An IVOM approach exploits compositional biases using variable order motif distributions and captures more reliably the local composition of a sequence compared to fixed-order methods. Optionally the predictions can be parsed into a 2-state 2nd order Hidden Markov Model (HMM), in a change-point detection framework, to optimize the localization of the boundaries of the predicted regions. The predictions (embl format) can be automatically loaded into Artemis genome viewer freely available at: http://www.sanger.ac.uk/Software/Artemis/.

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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altree
program to perform phylogeny-based association and localization analysis
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ALTree was designed to perform association detection and localization of susceptibility sites using haplotype phylogenetic trees: first, it allows the detection of an association between a candidate gene and a disease, and second, it enables to make hypothesis about the susceptibility loci.

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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ampliconnoise
454 시퀀싱 PCR 앰플리콘의 노이즈 제거
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AmpliconNoise는 높은 처리량의 시퀀스 데이타를 정리하는 어플리케이션 패키지 입니다. 3개의 메인 파트로 구성됩니다:

Pyronoise - 잘못 해석된 곳을 플로우그램 기반 클러스트링 처리 SeqNoise - PCR 포인트 변이 제거 Perseus - 레퍼런스 시퀀스 집합에 대한 필요가 없이 PCR 키메라 제거

이전에는 동일한 개발자가 만든 독립 실행형 "Pyronoise"가 있었고 이 패키지는 업데이트된 버젼을 포함합니다. Qiime에는 관련있는 "Denoiser"가 있지만 서로 별개입니다.

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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Topics: Sequencing
anfo
MPG의 단편 서열 정렬기/매퍼
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Anfo는 Soap/Maq/Bowtie 정신을 따르는 매퍼지만, 구현에는 BLAST/BLAT 이후 더 많은 시간이 걸립니다. 이는 DNS 시퀀스가 어떻게든 수정되거나 (고대 DNA 또는 중아황산염 처리를 생각) 빠른 매퍼가 정상적으로 처리하는 것보다 샘플과 참조 사이에 더 많은 차이가 있는 시퀀싱 읽기 정렬에 가장 유용합니다 (예: 참조 게놈이 누락되는 대신 관련 종이 사용됩니다)

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Topics: Sequencing
aragorn
tRNA and tmRNA detection in nucleotide sequences
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The program employs heuristic algorithms to predict tRNA secondary structure, based on homology with recognized tRNA consensus sequences and ability to form a base-paired cloverleaf. tmRNA genes are identified using a modified version of the BRUCE program.

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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Topics: Functional, regulatory and non-coding RNA
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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Topics: Sequencing
autodock
analysis of ligand binding to protein structure
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AutoDock is a prime representative of the programs addressing the simulation of the docking of fairly small chemical ligands to rather big protein receptors. Earlier versions had all flexibility in the ligands while the protein was kept rather ridgid. This latest version 4 also allows for a flexibility of selected sidechains of surface residues, i.e., takes the rotamers into account.

The AutoDock program performs the docking of the ligand to a set of grids describing the target protein. AutoGrid pre-calculates these grids.

The package is enhanced by the following packages: autogrid
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autodock-vina
docking of small molecules to proteins
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AutoDock Vina is a program to support drug discovery, molecular docking and virtual screening of compound libraries. It offers multi-core capability, high performance and enhanced accuracy and ease of use.

The same institute also developed autodock, which is widely used.

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
리간드와 수용체 결합을 미리 계산
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AutoDockSuite는 알려진 3차원 구조의 수용체에 대해서 더 작은 화합물의 도킹에 대한 분자 분석을 다룹니다.

AutoGrid 프로그램은 단백질이 점 전하에 미치는 영향을 설명하는 그리드 세트에 리간드를 도킹하기 위한 사전 계산을 수행합니다. 리간드에 대한 이러한 힘의 효과는 AutoDock 프로그램에 의해 분석됩니다.

bamtools
BAM (게놈 정렬) 파일을 조작하기 위한 툴킷
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BamTools은 BAM 파일을 사용해서 연국 분석 및 데이타 관리를 용이하게 합니다. 현재 시퀀싱 기술로 생성된 엄청난 양의 데이타를 처리합니다. 이 데이타는 생물 정보학 연구에서 일반적으로 사용되는 텍스트 기반 파서에 의해 쉽게 처리되지 않는 바이너리 형식, 일반적으로 압축된 상태로 저장됩니다.

BamTools는 BAM 파일 지원 및 명령행 툴킷 모두를 위한 C++ API를 제공합니다.

이 패키지는 bamtools 명령행 툴킷입니다.

사용 가능한 bamtools 명령:

 convert  BAM과 다른 여러 형식간 변환
 count    BAM 파일에서 정렬을 인쇄
 coverage 입력된 BAM 파일에서 범위 통계를 인쇄
 filter   사용자 지정 기준에 따라 BAM 파일 필터링
 header   BAM 헤더 정보 인쇄
 index    BAM 파일용 인덱스 생성
 merge    여러 BAM 파일을 하나의 파일로 병합
 random   기존의 BAM 파일에서 임의 정렬을 선택, 테스팅 도구로 더 많이
          사용.
 resolve  쌍방향 읽기 해결 (필요에 따라 IsProperPair 플래그 표시)
 revert   중복 마크 제거 및 원래 기본 품질 복구
 sort     몇몇 기준에 따라 BAM 파일 정렬
 split    사용자 지정 속성에서 BAM 파일 분할, 발견된 각 값에 대한
          새로운 BAM 출력 파일 생성
 stats    입력 BAM 파일에서 몇가지 기본 통계 인쇄
The package is enhanced by the following packages: multiqc
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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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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bioperl
Perl tools for computational molecular biology
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The Bioperl project is a coordinated effort to collect computational methods routinely used in bioinformatics into a set of standard CPAN-style, well-documented, and freely available Perl modules. It is well-accepted throughout the community and used in many high-profile projects, e.g., Ensembl.

The recommended packages are needed to run some of the included binaries, for a detailed explanation including the specific Perl modules please see README.Debian.

The suggested package enhances the manual pages.

Please cite: Jason E Stajich, David Block, Kris Boulez, Steven E Brenner, Stephen A Chervitz, Chris Dagdigian, Georg Fuellen, James G R Gilbert, Ian Korf, Hilmar Lapp, Heikki Lehvaslaiho, Chad Matsalla, Chris J Mungall, Brian I Osborne, Matthew R Pocock, Peter Schattner, Martin Senger, Lincoln D Stein, Elia Stupka, Mark D Wilkinson and Ewan Birney: The Bioperl toolkit: Perl modules for the life sciences. (PubMed,eprint) Genome Res. 12(10):1611-1618 (2002)
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bioperl-run
BioPerl wrappers: scripts
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Contains scripts from the BioPerl-Run package. This package will also install all wrappable applications packaged in Debian. The ones that are not Free are "Suggested" by this package.

The package is enhanced by the following packages: clustalw exonerate kalign mcl
biosquid
utilities for biological sequence analysis
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SQUID is a library of C code functions for sequence analysis. It also includes a number of small utility programs to convert, show statistics, manipulate and do other functions on sequence files.

The original name of the package is "squid", but since there is already a squid on the archive (a proxy cache), it was renamed to "biosquid".

This package contains some tools to demonstrate the features of the SQUID library.

blast2
transitional dummy package to ncbi-blast+-legacy
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This is a transitional dummy package for ncbi-blast+-legacy. It can safely be removed.

The package is enhanced by the following packages: mcl
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bowtie
초고속 메모리 효율적인 짧은 읽기 정렬기
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이 패키지는 최신 (2010) DNA 염기서열 분석 기술의 결과를 해석하기 위해 문제를 해결합니다. 이는 상당히 짧은 범위를 생성하며 작접적으로 해석할 수 없습니다. Bowtie와 같은 도구는 실행당 시퀀싱된 DNA의 짧은 길이에 염색체 위치를 제공하는 것은 어려운 일입니다.

Bowtie는 짧은 DNA 서열 (읽기)을 시간당 2,500만 개 이상의 35bp 시간당 읽기 속도로 인간 게놈에 정렬합니다. Bowtie는 메모리 공간을 작게 유지하기 위해 Burrows-Wheeler 인덱스로 게놈을 인덱스화합니다: 일반적으로 인간 게놈의 경우 2.2GB (페어드 엔드의 경우 2.9GB) 입니다.

The package is enhanced by the following packages: bowtie-examples multiqc
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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Topics: Genomics
bowtie2
ultrafast memory-efficient short read aligner
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is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters, and particularly good at aligning to relatively long (e.g. mammalian) genomes.

Bowtie 2 indexes the genome with an FM Index to keep its memory footprint small: for the human genome, its memory footprint is typically around 3.2 GB. Bowtie 2 supports gapped, local, and paired-end alignment modes

The package is enhanced by the following packages: bowtie2-examples multiqc
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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Topics: Genomics
boxshade
Pretty-printing of multiple sequence alignments
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Boxshade is a program for creating good looking printouts from multiple-aligned protein or DNA sequences. The program does not perform the alignment by itself and requires as input a file that was created by a multiple alignment program or manually edited with respective tools.

Boxshade reads multiple-aligned sequences from either PILEUP-MSF, CLUSTAL-ALN, MALIGNED-data and ESEE-save files (limited to a maximum of 150 sequences with up to 10000 elements each). Various kinds of shading can be applied to identical/similar residues. Output is written to screen or to a file in the following formats: ANSI/VT100, PS/EPS, RTF, HPGL, ReGIS, LJ250-printer, ASCII, xFIG, PICT, HTML

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bwa
Burrows-Wheeler Aligner
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BWA is a software package for mapping low-divergent sequences against a large reference genome, such as the human genome. It consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. The first algorithm is designed for Illumina sequence reads up to 100bp, while the rest two for longer sequences ranged from 70bp to 1Mbp. BWA-MEM and BWA-SW share similar features such as long-read support and split alignment, but BWA-MEM, which is the latest, is generally recommended for high-quality queries as it is faster and more accurate. BWA-MEM also has better performance than BWA-backtrack for 70-100bp Illumina reads.

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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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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cd-hit
suite of programs designed to quickly group sequences
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cd-hit contains a number of programs designed to quickly group sequences. cd-hit groups proteins into clusters that meet a user-defined similarity threshold. cd-hit-est is similar to cd-hit, but designed to group nucleotide sequences (without introns). cd-hit-est-2d is similar to cd-hit-2d but designed to compare two nucleotide datasets. A number of other related programs are also in this package. Please see the cd-hit user manual, also part of this package, for further information.

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Topics: Genomics
cdbfasta
Constant DataBase indexing and retrieval tools for multi-FASTA files
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CDB (Constant DataBase) can be used for creating indices for quick retrieval of any particular sequences from large multi-FASTA files. It has the option to compress data records in order to save space.

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circos
데이타를 시각화하는 플로터
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Circos는 원형 배치로 데이타를 시각화합니다 - 원형배치는 객체 또는 위치간 관 계 탐색 및 매우 유용한 출판 품질 그래픽을 만드는데 이상적입니다.

이 패키지는 (gnuplot와 같이) 명령행으로 구동되고 스크립트를 완벽하게 지원하 는 Circos 플로터 엔진을 제공합니다.

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
multilocus 시퀀스 데이터를 사용하여 세균 소진화 추론
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ClonalFrame은 클론 상속을 중단한 상동 재조합 이벤트 염색체 위치를 추정하면 서, 샘플 멤버들 사이에 클론 관계를 식별합니다.

전체 게놈에서 단일 조각 DNA를 통해, Clonalframe을 임의의 시퀀스 데이타에도 적용할 수 있습니다. 이는 7 유전자 단편이 시퀀스된, MLST 데이타 분석에 꽤 적 합하지만, 시퀀스된 영역이 전체 게놈에 길이와 수를 증가함으로 점차 더 강력해 집니다. 하지만 이는 정렬된 시퀀스를 요구합니다. 정렬되지 않은 게놈 데이타를 가지고 있을 경우, ClonalFrame 분석에 필요한 정확한 형식으로 전체 박테리아 게놈을 정렬하는 Mauve 사용을 권장합니다.

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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clustalo
General-purpose multiple sequence alignment program for proteins
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Clustal Omega is a general-purpose multiple sequence alignment (MSA) program, primarily for amino-acid sequences. It produces high quality MSAs and is capable of handling data sets of hundreds of thousands of sequences in reasonable time, using multiple processors where available.

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,eprint) Molecular Systems Biology 7:539 (2011)
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clustalw
global multiple nucleotide or peptide sequence alignment
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This program performs an alignment of multiple nucleotide or amino acid sequences. It recognizes the format of input sequences and whether the sequences are nucleic acid (DNA/RNA) or amino acid (proteins). The output format may be selected from in various formats for multiple alignments such as Phylip or FASTA. Clustal W is very well accepted.

The output of Clustal W can be edited manually but preferably with an alignment editor like SeaView or within its companion Clustal X. When building a model from your alignment, this can be applied for improved database searches. The Debian package hmmer creates such in form of an 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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Topics: Sequence analysis
concavity
predictor of protein ligand binding sites from structure and conservation
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ConCavity predicts protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

ConCavity takes as input a PDB format protein structure and optionally files that characterize the evolutionary sequence conservation of the chains in the structure file.

The following result files are produced by default:

  • Residue ligand binding predictions for each chain (*.scores).
  • Residue ligand binding predictions in a PDB format file (residue scores placed in the temp. factor field, *_residue.pdb).
  • Pocket prediction locations in a DX format file (*.dx).
  • PyMOL script to visualize the predictions (*.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
protein sequence conservation scoring tool
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This package provides score_conservation(1), a tool to score protein sequence conservation.

The following conservation scoring methods are implemented:

  • sum of pairs
  • weighted sum of pairs
  • Shannon entropy
  • Shannon entropy with property groupings (Mirny and Shakhnovich 1995, Valdar and Thornton 2001)
  • relative entropy with property groupings (Williamson 1995)
  • von Neumann entropy (Caffrey et al 2004)
  • relative entropy (Samudrala and Wang 2006)
  • Jensen-Shannon divergence (Capra and Singh 2007)

A window-based extension that incorporates the estimated conservation of sequentially adjacent residues into the score for each column is also given. This window approach can be applied to any of the conservation scoring methods.

The program accepts alignments in the CLUSTAL and FASTA formats.

The sequence-specific output can be used as the conservation input for concavity.

Conservation is highly predictive in identifying catalytic sites and residues near bound ligands.

Please cite: John A. Capra and Mona Singh: Predicting functionally important residues from sequence conservation. (PubMed) Bioinformatics 23(15):1875-82 (2007)
datamash
명령행 인터페이스용 통계 도구
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GNU Datamash는 입력 텍스트 데이타 파일에서 기본 숫자, 텍스트 및 통계 연산을 수행하는 명령행 프로그램입니다. 이식 가능하고 신뢰있게 설계되었으며, 연구원이 코드 또는 짧은 스크립트를 만들지 않고도 분석 파이프라인을 쉽게 자동화 할 수 있도록 합니다.

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dialign
Segment-based multiple sequence alignment
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DIALIGN2 is a command line tool to perform multiple alignment of protein or DNA sequences. It constructs alignments from gapfree pairs of similar segments of the sequences. This scoring scheme for alignments is the basic difference between DIALIGN and other global or local alignment methods. Note that DIALIGN does not employ any kind of gap penalty.

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
Segment-based multiple sequence alignment
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DIALIGN-TX is a command line tool to perform multiple alignment of protein or DNA sequences. It is a complete reimplementation of the segment-base approach including several new improvements and heuristics that significantly enhance the quality of the output alignments compared to DIALIGN 2.2 and DIALIGN-T. For pairwise alignment, DIALIGN-TX uses a fragment-chaining algorithm that favours chains of low-scoring local alignments over isolated high-scoring fragments. For multiple alignment, DIALIGN-TX uses an improved greedy procedure that is less sensitive to spurious local sequence similarities.

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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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
시스테인 이황화 결합 상태 및 연결 예측자
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'disulfinder'는 시스테인의 이황화 결합 상태와 염기 서열만으로 시작하는 이들의 이황화 연결성을 예측하기위한 것입니다. 이황화 가교는 여러 단백질의 폴딩 과정을 안정화하는 데 중요한 역할을합니다. 따라서 서열만으로 이황화 가교를 예측하는 것은 특정 단백질의 구조 및 기능적 특성을 연구하는 데 유용합니다. 또한 시스테인의 이황화 결합 상태에 대한 지식은 실험 구조 결정 과정에 도움이 될 수 있으며 다른 게놈 주석 작업에 유용 할 수 있습니다.

'disulfinder'는 두 가지 계산 단계에서 이황화 패턴을 예측합니다: (1) 각 시스테인의 이황화 결합 상태는 BRNN-SVM 이원 분류기에 의해 예측됩니다. (2) 브리지 형성에 참여하는 것으로 알려진 시스테인은 연결 패턴을 얻기 위해 재귀 신경망에 의해 쌍을 이룹니다.

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):W177-181 (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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dssp
protein secondary structure assignment based on 3D structure
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DSSP is an application you use to assign the secondary structure of a protein based on its solved three dimensional (3D) structure.

This version (4.2) of DSSP is a rewrite that writes annotated mmCIF files by default but can still produce the older dssp format. New is also the support of PP helices.

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embassy-domainatrix
Extra EMBOSS commands to handle domain classification file
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The DOMAINATRIX programs were developed by Jon Ison and colleagues at MRC HGMP for their protein domain research. They are included as an EMBASSY package as a work in progress.

Applications in the current domainatrix release are cathparse (generates DCF file from raw CATH files), domainnr (removes redundant domains from a DCF file), domainreso (removes low resolution domains from a DCF file), domainseqs (adds sequence records to a DCF file), domainsse (adds secondary structure records to a DCF file), scopparse (generates DCF file from raw SCOP files) and ssematch (searches a DCF file for secondary structure matches).

embassy-domalign
Extra EMBOSS commands for protein domain alignment
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The DOMALIGN programs were developed by Jon Ison and colleagues at MRC HGMP for their protein domain research. They are included as an EMBASSY package as a work in progress.

Applications in the current domalign release are allversusall (sequence similarity data from all-versus-all comparison), domainalign (generates alignments (DAF file) for nodes in a DCF file), domainrep (reorders DCF file to identify representative structures) and seqalign (extend alignments (DAF file) with sequences (DHF file)).

embassy-domsearch
Extra EMBOSS commands to search for protein domains
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The DOMSEARCH programs were developed by Jon Ison and colleagues at MRC HGMP for their protein domain research. They are included as an EMBASSY package as a work in progress.

Applications in this DOMSEARCH release are seqfraggle (removes fragment sequences from DHF files), seqnr (removes redundancy from DHF files), seqsearch (generates PSI-BLAST hits (DHF file) from a DAF file), seqsort (Remove ambiguous classified sequences from DHF files) and seqwords (Generates DHF files from keyword search of 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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exonerate
generic tool for pairwise sequence comparison
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Exonerate allows you to align sequences using a many alignment models, using either exhaustive dynamic programming, or a variety of heuristics. Much of the functionality of the Wise dynamic programming suite was reimplemented in C for better efficiency. Exonerate is an intrinsic component of the building of the Ensembl genome databases, providing similarity scores between RNA and DNA sequences and thus determining splice variants and coding sequences in general.

An In-silico PCR Experiment Simulation System (see the ipcress man page) is packaged with exonerate.

This package also comes with a selection of utilities for performing simple manipulations quickly on fasta files beyond 2Gb

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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fastdnaml
Tool for construction of phylogenetic trees of DNA sequences
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fastDNAml is a program derived from Joseph Felsenstein's version 3.3 DNAML (part of his PHYLIP package). Users should consult the documentation for DNAML before using this program.

fastDNAml is an attempt to solve the same problem as DNAML, but to do so faster and using less memory, so that larger trees and/or more bootstrap replicates become tractable. Much of fastDNAml is merely a recoding of the PHYLIP 3.3 DNAML program from PASCAL to C.

Note that the homepage of this program is not available any more and so this program will probably not see any further updates.

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)
fastlink
기존의 Linkage 보다 더 빠른 버젼
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유전자 연관 분석은 유전자 지도 및 유전자 질병의 대략적인 위치를 찾는데 사용 되는 통계적 기법입니다. LINKAGE라 불리는 유전적 연관을 위한 표준 소프트웨어 패키지가 있습니다. FASTLINK는 더 빠르게 순차적으로 실행되고, 병렬로 실행할 수 있으며, 컴퓨터 문제에서 사용자가 정상적으로 복구 할 수 있도록 하며, 그리 고 풍부한 새로운 문서를 제공하는 LINKAGE 메인 프로그램의 크게 개선된 버젼입 니다. FASTLINK는 1000개 이상의 발표된 유전적 연관 연구를 통해 사용되어 왔습 니다.

이 패키지는 다음과 같은 프로그램이 포함되어 있습니다:

 iLink: 조환비율 벡터의 내부적 세타 최적값을 찾기 위한 GEMINI 최적화 절차
 linkmap: 다른 유전자자리들의 고정된 지도에 대한 하나의 유전자자리의 위치
          점수 계산
 lodscore: 내부 최적 세타에서 가능성 비교
 MLINK: LOD 점수와 두개의 더 많은 유전자자리 위험 계산
 unknown: 알려지지 않은 것을 위해 가능한 유전형을 확인
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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fastqc
높은 처리량 시퀀스 데이타를 위한 품질 관리
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FastQC는 처리량이 높은 시퀀스 파이프라인에서 발생하는, 원시 시퀀스 데이타에 대한 몇가지 품질 관리 검사를 간단하게 수행할 수 있는 방법을 제공합니다. 추가 분석을 수행하기 전에 데이타에 알아야 할 문제가 있는지 여부를 신속하게 파악할 수 있는 모듈식 분석 집합을 제공합니다.

FastQC의 주요기능은 아래와 같습니다.

  • BAM, SAM 또는 FastQ 파일에서 데이타 가져오기 (모든 변형)
  • 문제가 발생할 수 있는 영역을 당신에게 알려줄 빠른 개요 제공
  • 데이타를 빠르게 평가 할 수 있는 요약 그래프 및 테이블
  • 결과를 HTML 기반 영구 보고서로 내보내기
  • 대화형 어플리케이션을 실행하지 않고도 보고서를 자동으로 생성할 수 있는 오프라인 작업
The package is enhanced by the following packages: multiqc
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Topics: Sequencing
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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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.

The package is enhanced by the following packages: multiqc
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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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)
Topics: Structure prediction; Sequence analysis
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.

The package is enhanced by the following packages: gasic-examples
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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genometools
versatile genome analysis toolkit
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The GenomeTools contains a collection of useful tools for biological sequence analysis and -presentation combined into a single binary.

The toolkit contains binaries for sequence and annotation handling, sequence compression, index structure generation and access, annotation visualization, and much more.

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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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
produces PostScript graphical output from GFF-files
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gff2ps is a script program developed with the aim of converting gff-formatted records into high quality one-dimensional plots in PostScript. Such plots maybe useful for comparing genomic structures and to visualizing outputs from genome annotation programs. It can be used in a very simple way, because it assumes that the GFF file itself carries enough formatting information, but it also allows through a number of options and/or a configuration file, for a great degree of customization.

Please cite: J. F. Abril and R. Guigó: gff2ps: visualizing genomic annotations.. (PubMed,eprint) Bioinformatics 16(8):743-744 (2000)
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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
gapped protein motifs from unaligned sequences
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GLAM2 is a software package for finding motifs in sequences, typically amino-acid or nucleotide sequences. A motif is a re-occurring sequence pattern: typical examples are the TATA box and the CAAX prenylation motif. The main innovation of GLAM2 is that it allows insertions and deletions in motifs.

This package includes programs for discovering motifs shared by a set of sequences and finding matches to these motifs in a sequence database, as well as utilities for converting glam2 motifs to standard alignment formats, masking glam2 motifs out of sequences so that weaker motifs can be found, and removing highly similar members of a set of sequences.

The package includes these programs:

 glam2:       discovering motifs shared by a set of sequences;
 glam2scan:   finding matches, in a sequence database, to a motif discovered
              by glam2;
 glam2format: converting glam2 motifs to  standard alignment formats;
 glam2mask:   masking glam2 motifs out of sequences, so that weaker motifs
              can be found;
 glam2-purge: removing highly similar members of a set of sequences.

In this binary package, the fast Fourier algorithm (FFT) was enabled for the glam2 program.

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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gmap
spliced and SNP-tolerant alignment for mRNA and short reads
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This package contains the programs GMAP and GSNAP as well as utilities to manage genome databases in GMAP/GSNAP format. GMAP (Genomic Mapping and Alignment Program) is a tool for aligning EST, mRNA and cDNA sequences. GSNAP (Genomic Short-read Nucleotide Alignment Program) is a tool for aligning single-end and paired-end transcriptome reads. Both tools can use a database of

  • known splice sites and identify novel splice sites.
  • known single-nucleotide polymorphisms (SNPs). GSNAP can align bisulfite-treated DNA.
Please cite: Thomas D. Wu and Serban Nacu: Fast and SNP-tolerant detection of complex variants and splicing in short reads. (PubMed,eprint) Bioinformatics 26(7):873-81 (2010)
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grinder
Versatile omics shotgun and amplicon sequencing read simulator
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Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file.

Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.

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
Molecular dynamics simulator, with building and analysis tools
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GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.

It is primarily designed for biochemical molecules like proteins and lipids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non- biological systems, e.g. polymers.

This package contains variants both for execution on a single machine, and using the MPI interface across multiple machines.

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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hhsuite
sensitive protein sequence searching based on HMM-HMM alignment
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HH-suite is an open-source software package for sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs).

This package contains HHsearch and HHblits among other programs and utilities.

HHsearch takes as input a multiple sequence alignment (MSA) or profile HMM and searches a database of HMMs (e.g. PDB, Pfam, or InterPro) for homologous proteins. HHsearch is often used for protein structure prediction to detect homologous templates and to build highly accurate query-template pairwise alignments for homology modeling.

HHblits can build high-quality MSAs starting from single sequences or from MSAs. It transforms these into a query HMM and, using an iterative search strategy, adds significantly similar sequences from the previous search to the updated query HMM for the next search iteration. Compared to PSI-BLAST, HHblits is faster, up to twice as sensitive and produces more accurate 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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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).

The package is enhanced by the following packages: multiqc
Please cite: Daehwan Kim, Joseph M. Paggi, Chanhee Park, Christopher Bennett and Steven L. Salzberg: Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nature Biotechnology 37(8):907-915 (2019)
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hmmer
profile hidden Markov models for protein sequence analysis
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HMMER is an implementation of profile hidden Markov model methods for sensitive searches of biological sequence databases using multiple sequence alignments as queries.

Given a multiple sequence alignment as input, HMMER builds a statistical model called a "hidden Markov model" which can then be used as a query into a sequence database to find (and/or align) additional homologues of the sequence family.

Please cite: S. R. Eddy: Profile hidden Markov models. (PubMed,eprint) Bioinformatics 14(9):755-763 (1998)
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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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infernal
inference of RNA secondary structural alignments
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Infernal ("INFERence of RNA ALignment") searches DNA sequence databases for RNA structure and sequence similarities. It provides an implementation of a special variant of profile stochastic context-free grammars called covariance models (CMs). A CM is like a sequence profile, but it scores a combination of sequence consensus and RNA secondary structure consensus, so in many cases, it is more capable of identifying RNA homologs that conserve their secondary structure more than their primary sequence.

The tool is an integral component of the Rfam database.

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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jellyfish
count k-mers in DNA sequences
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JELLYFISH is a tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence. JELLYFISH can count k-mers using an order of magnitude less memory and an order of magnitude faster than other k-mer counting packages by using an efficient encoding of a hash table and by exploiting the "compare-and-swap" CPU instruction to increase parallelism.

JELLYFISH is a command-line program that reads FASTA and multi-FASTA files containing DNA sequences. It outputs its k-mer counts in an binary format, which can be translated into a human-readable text format using the "jellyfish dump" command.

The package is enhanced by the following packages: multiqc
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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kalign
Global and progressive multiple sequence alignment
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Kalign is a command line tool to perform multiple alignment of biological sequences. It employs the Muth-Manber string-matching algorithm, to improve both the accuracy and speed of the alignment. It uses global, progressive alignment approach, enriched by employing an approximate string-matching algorithm to calculate sequence distances and by incorporating local matches into the otherwise global alignment.

Please cite: Lassmann, Timo.: Kalign 3: multiple sequence alignment of large datasets. (eprint) Bioinformatics 36(6):1928-1929 (2020)
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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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Topics: RNA-seq; RNA splicing; Gene structure
last-align
genome-scale comparison of biological sequences
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LAST is software for comparing and aligning sequences, typically DNA or protein sequences. LAST is similar to BLAST, but it copes better with very large amounts of sequence data. Here are two things LAST is good at:

  • Comparing large (e.g. mammalian) genomes.
  • Mapping lots of sequence tags onto a genome.

The main technical innovation is that LAST finds initial matches based on their multiplicity, instead of using a fixed size (e.g. BLAST uses 10-mers). This allows one to map tags to genomes without repeat-masking, without becoming overwhelmed by repetitive hits. To find these variable-sized matches, it uses a suffix array (inspired by Vmatch). To achieve high sensitivity, it uses a discontiguous suffix array, analogous to 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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loki
MCMC linkage analysis on general pedigrees
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Performs Markov chain Monte Carlo multipoint linkage analysis on large, complex pedigrees. The current package supports analyses on quantitative traits only, although this restriction will be lifted in later versions. Joint estimation of QTL number, position and effects uses Reversible Jump MCMC. It is also possible to perform affected only IBD sharing analyses.

The package is enhanced by the following packages: loki-doc
macs
Model-based Analysis of ChIP-Seq on short reads sequencers
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MACS empirically models the length of the sequenced ChIP fragments, which tends to be shorter than sonication or library construction size estimates, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome sequence, allowing for more sensitive and robust prediction. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, is publicly available open source, and can be used for ChIP-Seq with or without control samples.

Please cite: Yong Zhang, Tao Liu, Clifford A Meyer, Jérôme Eeckhoute, David S. Johnson, Bradley E. Bernstein, Chad Nussbaum, Richard M. Myers, Myles Brown, Wei Li and X Shirley Liu: Model-based Analysis of ChIP-Seq (MACS). (PubMed,eprint) Genome Biol. 9(9):R137 (2008)
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mafft
Multiple alignment program for amino acid or nucleotide sequences
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MAFFT is a multiple sequence alignment program which offers three accuracy-oriented methods:

  • L-INS-i (probably most accurate; recommended for <200 sequences; iterative refinement method incorporating local pairwise alignment information),
  • G-INS-i (suitable for sequences of similar lengths; recommended for <200 sequences; iterative refinement method incorporating global pairwise alignment information),
  • E-INS-i (suitable for sequences containing large unalignable regions; recommended for <200 sequences), and five speed-oriented methods:

  • FFT-NS-i (iterative refinement method; two cycles only),

  • FFT-NS-i (iterative refinement method; max. 1000 iterations),
  • FFT-NS-2 (fast; progressive method),
  • FFT-NS-1 (very fast; recommended for >2000 sequences; progressive method with a rough guide tree),
  • NW-NS-PartTree-1 (recommended for ∼50,000 sequences; progressive method with the PartTree algorithm).
Please cite: Kazutaka Katoh and Hiroyuki Toh: Recent developments in the MAFFT multiple sequence alignment program. (PubMed) Brief Bioinform 9(4):286-298 (2008)
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mapsembler2
bioinformatics targeted assembly software
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Mapsembler2 is a targeted assembly software. It takes as input a set of NGS raw reads (fasta or fastq, gzipped or not) and a set of input sequences (starters).

It first determines if each starter is read-coherent, e.g. whether reads confirm the presence of each starter in the original sequence. Then for each read-coherent starter, Mapsembler2 outputs its sequence neighborhood as a linear sequence or as a graph, depending on the user choice.

Mapsembler2 may be used for (not limited to):

  • Validate an assembled sequence (input as starter), e.g. from a de Bruijn graph assembly where read-coherence was not enforced.
  • Checks if a gene (input as starter) has an homolog in a set of reads
  • Checks if a known enzyme is present in a metagenomic NGS read set.
  • Enrich unmappable reads by extending them, possibly making them mappable
  • Checks what happens at the extremities of a contig
  • Remove contaminants or symbiont reads from a read set
Please cite: Pierre Peterlongo and Rayan Chikhi: Mapsembler, targeted and micro assembly of large NGS datasets on a desktop computer. (PubMed) BMC Bioinformatics 13:48 (2012)
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maq
maps short fixed-length polymorphic DNA sequence reads to reference sequences
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Maq (short for Mapping and Assembly with Quality) builds mapping assemblies from short reads generated by the next-generation sequencing machines. It was particularly designed for Illumina-Solexa 1G Genetic Analyzer, and has a preliminary functionality to handle ABI SOLiD data. Maq is previously known as mapass2.

Developmemt of Maq stopped in 2008. Its successors are BWA and SAMtools.

Please cite: Heng Li, Jue Ruan and Richard Durbin: Mapping short DNA sequencing reads and calling variants using mapping quality scores. (PubMed,eprint) Genome Research 18(11):1851-1858 (2008)
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melting
핵산 듀플렉스의 용해 온도 계산
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이 프로그램은 핵산 듀플렉스, 엔탈피, 엔트로피, 그리고 나선 코일 변화의 용해 온도를 계산합니다. 3가지 타입의 교배가 가능합니다: DNA/DNA, DNA/RNA, 그리고 RNA/RNA. 이 프로그램은 먼저 최단 거리법을 사용해서 각각의 Crick 쌍의 원소 파라미터로 부터 교배 엔탈피와 엔트로피를 계산합니다. 그 다음 용해 온도가 계 산됩니다. 열역학적 파라미터 군은 쉽게 바뀔 수 있습니다, 예를 들면 실험적인 비약적 발전.

Please cite: Le Novère, Nicolas: MELTING, computing the melting temperature of nucleic acid duplex. (PubMed,eprint) Bioinformatics 17(12):1226-1227 (2001)
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minia
short-read biological sequence assembler
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What was referred to as "next-generation" DNA sequencing up to the year 2020 delivered only "short" reads up to ~600 base pairs in length that would then have to be puzzled by random overlaps in their sequence towards a complete genome. This is the genome assembly. And there are many biological pitfalls on long stretches of low complexity regions and copy number variations and other sorts of redundancies that render this difficult.

This package provides a short-read DNA sequence assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day.

The output of Minia is a set of contigs, i.e. stretches of gap-free linear overlaps of short reads. In the best possible case this is a whole chromosome.

Minia produces results of similar contiguity and accuracy to other de Bruijn assemblers (e.g. Velvet).

Please cite: Rayan Chikhi and Guillaume Rizk: Space-Efficient and Exact de Bruijn Graph Representation Based on a Bloom Filter.. (PubMed,eprint) Algorithms for Molecular Biology 8(1):22 (2013)
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mipe
PCR 파생 데이타 저장 도구
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MIPE는 일반 텍스트 파일을 사용하는 PCR 실험과 관련된 모든 정보의 교환 또는 저장하기 위한 표준 포맷을 제공합니다. 이 프로그램은 다음의 기능을 제공합니다:

  • 연구자/연구소간에 PCR 데이타 교환 허용
  • 데이타의 추적 활성
  • dbSTS 또는 dbSNP로 데이타를 제출할 때 발생할 수 있는 문제 방지
  • 데이타 (예. PCR 안내 리스트, 다른 동물들을 위한 SNP 위치 또는 haplotypes) 추출을 위한 표준 스크립트의 작성 활성

이 툴이 비록 데이타 저장에 사용될 수 있지만, 데이타 교환에 중점을 두고 있습니다. 대규모 저장소를 위해, 관계 데이타베이스(RDB)가 데이타 저장에 더 적합합니다. MIPE 포맷은 이러한 데이타베이스에서 임포트나 또는 데이타베이스로 익스포트를 위한 표준적 포맷으로 사용될 수 있습니다.

Please cite: Jan Aerts and T. Veenendaal: MIPE - a XML-format to facilitate the storage and exchange of PCR-related data. Online Journal of Bioinformatics 6(2):114-120 (2005)
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mira-assembler
전체 게놈 샷건 및 EST 시퀀스 어셈블러
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mira 게놈 조각 어셈블러는 많은 양의 유사한 반복으로 'hard'로 분류된 시퀀싱 프로젝트에 전문화된 어셈블러입니다. 명시적 시퀀스 태그 (ESTs) 전사물을 위 해, miraEST는 상이한 변이체에서 발생하는 단일 뉴클레오타이드 다형성 (SNP)을 검출하고 분류하는 동안 원래의 mRNA 전사물을 재구성하는데 특화되어 있습니다.

어셈블러는 상이한 세포 유형에서의 돌연변이 검출, 유기체 간의 전사물의 유사 성 분석, 임상 미세배열 실험에서 올리고 디자인을 위한 다양한 출처의 시퀀스 초기 어셈블리같은 다양한 작업에서 일상적으로 사용됩니다.

패키지는 다음 실행파일을 제공합니다: 제공되는 바이너리:

  • mira: 게놈 시퀀스의 어셈블리를 위해
  • miramem: 어셈블 프로젝트에 필요한 메모리 계산.
  • mirabait: 256 개의 베이스까지 kmers로 읽기를 선택하는 "grep"과 유사한 도구
  • miraconvert: 시퀀스 어셈블리 파일과 관련된 모든 종류의 데이타를 변환, 추출, 때대로 재계산하는 도구.
Please cite: Bastien Chevreux, Thomas Pfisterer, Bernd Drescher, Albert J. Driesel, Werner E. G. Müller, Thomas Wetter and Sándor Suhai: Using the miraEST Assembler for Reliable and Automated mRNA Transcript Assembly and SNP Detection in Sequenced ESTs. (PubMed,eprint) Genome Research 14(6):1147-1159 (2004)
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mlv-smile
Find statistically significant patterns in sequences
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Smile determines sequence motifs on the basis of a set of DNA, RNA or protein sequences.

  • No hard limit on the number of combinations of motifs to describe subsets of sequences.
  • The sequence alphabet may be specified.
  • The use of wildcards is supported.
  • Better determination of significance of motifs by simulation.
  • Introduction of a set of sequences with negative controls that should not match automatically determined motifs.
mothur
미생물학 연구를 위한 서열 분석 모음
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Mothur는 미생물 생태계 공동체의 생물 정보학 요구를 충족시키기 위해 오픈 소 스, 확장가능한 소프트웨어의 단일 버전을 개발하려고 합니다. dotur, sons, treeclimber, s-libshuff, unifrac 및 그 이상의 기능을 통합했습니다. 이러한 알고리즘 유연성 확장외에도, 계산기 및 시각화 도구f르 포함한 여러가지 기능이 추가되었습니다.

Please cite: Patrick D Schloss, Sarah L Westcott, Thomas Ryabin, Justine R Hall, Martin Hartmann, Emily B Hollister, Ryan A Lesniewski, Brian B Oakley, Donovan H Parks, Courtney J Robinson, Jason W Sahl, Blaz Stres, Gerhard G Thallinger, David J Van Horn and Carolyn F Weber: Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. (PubMed) Appl Environ Microbiol 75(23):7537-7541 (2009)
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Topics: Microbial ecology
mrbayes
Bayesian Inference of Phylogeny
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Bayesian inference of phylogeny is based upon a quantity called the posterior probability distribution of trees, which is the probability of a tree conditioned on the observations. The conditioning is accomplished using Bayes's theorem. The posterior probability distribution of trees is impossible to calculate analytically; instead, MrBayes uses a simulation technique called Markov chain Monte Carlo (or MCMC) to approximate the posterior probabilities of trees.

The package is enhanced by the following packages: mrbayes-doc
Please cite: Fredrik Ronquist, Maxim Teslenko, Paul van der Mark, Daniel L. Ayres, Aaron Darling, Sebastian Höhna, Bret Larget, Liang Liu, Marc A. Suchard and John P. Huelsenbeck: MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice across a Large Model Space. (PubMed,eprint) Systematic Biology (2012)
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mummer
Efficient sequence alignment of full genomes
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MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form. For example, MUMmer 3.0 can find all 20-basepair or longer exact matches between a pair of 5-megabase genomes in 13.7 seconds, using 78 MB of memory, on a 2.4 GHz Linux desktop computer. MUMmer can also align incomplete genomes; it handles the 100s or 1000s of contigs from a shotgun sequencing project with ease, and will align them to another set of contigs or a genome using the NUCmer program included with the system. If the species are too divergent for DNA sequence alignment to detect similarity, then the PROmer program can generate alignments based upon the six-frame translations of both input sequences.

The package is enhanced by the following packages: e-mem
Please cite: Stefan Kurtz, Adam Phillippy, Arthur L. Delcher, Michael Smoot, Martin Shumway, Corina Antonescu and Steven L. Salzberg: Versatile and open software for comparing large genomes. (PubMed) Genome Biology 5(2):R12 (2004)
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muscle
Multiple alignment program of protein sequences
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MUSCLE is a multiple alignment program for protein sequences. MUSCLE stands for multiple sequence comparison by log-expectation. In the authors tests, MUSCLE achieved the highest scores of all tested programs on several alignment accuracy benchmarks, and is also one of the fastest programs out there.

Muscle v5 is a major re-write of MUSCLE based on new algorithms.

Users should be aware that command line arguments compared to version 3.x of MUSCLE have changed!

Highest accuracy, scalable to thousands of sequences

Compared to previous versions, Muscle v5 is much more accurate, is often faster, and scales to much larger datasets. At the time of writing (late 2021), Muscle v5 has the highest scores on multiple alignment benchmarks including Balibase, Bralibase, Prefab and Balifam. It can align tens of thousands of sequences with high accuracy on a low-cost commodity computer (say, an 8-core Intel CPU with 32 Gb RAM). On large datasets, Muscle v5 is 20-30% more accurate than MAFFT and Clustal-Omega.

Alignment ensembles

Muscle v5 can generate ensembles of high-accuracy alternative alignments. All replicates have equal average accuracy on benchmark test, including the MSA made with default parameters. By comparing results of downstream analysis (trees, structure prediction...) on different replicates, you can assess the effects of alignment errors on your study.

Please cite: Robert C. Edgar: MUSCLE: multiple sequence alignment with high accuracy and high throughput. (PubMed,eprint) Nucleic Acids Research 32(5):1792-1797 (2004)
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Topics: Sequence analysis
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muscle3
multiple alignment program of protein sequences
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MUSCLE is a multiple alignment program for protein sequences. MUSCLE stands for multiple sequence comparison by log-expectation. In the authors tests, MUSCLE achieved the highest scores of all tested programs on several alignment accuracy benchmarks, and is also one of the fastest programs out there.

This is version 3 of the muscle program. It is a different program than muscle version 5 which is packaged as muscle in Debian.

Please cite: Robert C. Edgar: MUSCLE: multiple sequence alignment with high accuracy and high throughput. (PubMed,eprint) Nucleic Acids Research 32(5):1792-1797 (2004)
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Topics: Sequence analysis
mustang
multiple structural alignment of proteins
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Mustang is an algorithm to align multiple protein structures. Given a set of PDB files, the program uses the spatial information in the Calpha atoms of the set to produce a sequence alignment. Based on a progressive pairwise heuristic the algorithm then proceeds through a number of refinement passes. Mustang reports the multiple sequence alignment and the corresponding superposition of structures.

The package is enhanced by the following packages: mustang-testdata
Please cite: Arun S. Konagurthu, James C. Whisstock, Peter J. Stuckey and Arthur M. Lesk: MUSTANG: A multiple structural alignment algorithm. (PubMed) Proteins: Structure, Function, and Bioinformatics 64(3):559-574 (2006)
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ncbi-epcr
Tool to test a DNA sequence for the presence of sequence tagged sites
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Electronic PCR (e-PCR) is computational procedure that is used to identify sequence tagged sites(STSs), within DNA sequences. e-PCR looks for potential STSs in DNA sequences by searching for subsequences that closely match the PCR primers and have the correct order, orientation, and spacing that could represent the PCR primers used to generate known STSs.

The new version of e-PCR implements a fuzzy matching strategy. To reduce likelihood that a true STS will be missed due to mismatches, multiple discontiguous words may be used instead of a single exact word. Each of this word has groups of significant positions separated by 'wildcard' positions that are not required to match. In addition, it is also possible to allow gaps in the primer alignments.

The main motivation for implementing reverse searching (called Reverse e-PCR) was to make it feasible to search the human genome sequence and other large genomes. The new version of e-PCR provides a search mode using a query sequence against a sequence database.

This program is retired upstream and it is suggested to use Primer-Blast

 https://www.ncbi.nlm.nih.gov/tools/primer-blast/
instead.
Please cite: Gregory D. Schuler: Sequence Mapping by Electronic PCR. (PubMed,eprint) Genome Research 7(5):541-550 (1997)
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ncbi-tools-bin
NCBI libraries for biology applications (text-based utilities)
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This package includes various utilities distributed with the NCBI C SDK, including the development tools asntool and errhdr (formerly of libncbi6-dev). None of the programs in this package require X; you can find the X-based utilities in the ncbi-tools-x11 package. BLAST and related tools now come from a separate source base, corresponding to the ncbi-blast+ and ncbi-blast+-legacy packages.

The package is enhanced by the following packages: mcl
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ncoils
coiled coil secondary structure prediction
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The program predicts the coiled coil secondary structure predictions from protein sequences. The algorithm was published in Lupas, van Dyke & Stock, Predicting coiled coils from protein sequences Science, 252, 1162-1164, 1991.

Please cite: Andrei Lupas, Marc Van Dyke and Jeff Stock: Predicting coiled coils from protein sequences. (PubMed) Science 252:1162-1164 (1991)
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neobio
computes alignments of amino acid and nucleotide sequences
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Library and graphical user interface for pairwise sequence alignments. Implementation of the dynamic programming methods of Needleman & Wunsch (global alignment) and Smith & Waterman (local alignment).

Please cite: Maxime Crochemore, Gad M. Landau and Michal Ziv-Ukelson: A sub-quadratic sequence alignment algorithm for unrestricted cost matrices. :679-688 (2002)
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paraclu
Parametric clustering of genomic and transcriptomic features
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Paraclu finds clusters in data attached to sequences. It was first applied to transcription start counts in genome sequences, but it could be applied to other things too.

Paraclu is intended to explore the data, imposing minimal prior assumptions, and letting the data speak for itself.

One consequence of this is that paraclu can find clusters within clusters. Real data sometimes exhibits clustering at multiple scales: there may be large, rarefied clusters; and within each large cluster there may be several small, dense clusters.

Please cite: Martin C. Frith, Eivind Valen, Anders Krogh, Yoshihide Hayashizaki, Piero Carninci and Albin Sandelin: A code for transcription initiation in mammalian genomes. (eprint) Genome Research 18(1):1-12 (2008)
parsinsert
Parsimonious Insertion of unclassified sequences into phylogenetic trees
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ParsInsert efficiently produces both a phylogenetic tree and taxonomic classification for sequences for microbial community sequence analysis. This is a C++ implementation of the Parsimonious Insertion algorithm.

The package is enhanced by the following packages: parsinsert-testdata
pdb2pqr
Preparation of protein structures for electrostatics calculations
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PDB2PQR is a Python software package that automates many of the common tasks of preparing structures for continuum electrostatics calculations. It thus provides a platform-independent utility for converting protein files in PDB format to PQR format. These tasks include:

  • Adding a limited number of missing heavy atoms to biomolecular structures
  • Determining side-chain pKas
  • Placing missing hydrogens
  • Optimizing the protein for favorable hydrogen bonding
  • Assigning charge and radius parameters from a variety of force fields
Please cite: Todd J Dolinsky, Paul Czodrowski, Hui Li, Jens E Nielsen, Jan H Jensen, Gerhard Klebe and Nathan A Baker: PDB2PQR: Expanding and upgrading automated preparation of biomolecular structures for molecular simulations. (PubMed,eprint) Nucleic Acids Research 35:W522-5 (2007)
perm
efficient mapping of short reads with periodic spaced seeds
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PerM is a software package which was designed to perform highly efficient genome scale alignments for hundreds of millions of short reads produced by the ABI SOLiD and Illumina sequencing platforms. Today PerM is capable of providing full sensitivity for alignments within 4 mismatches for 50bp SOLID reads and 9 mismatches for 100bp Illumina reads.

Please cite: Yangho Chen, Tade Souaiaia and Ting Chen: PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds. (PubMed,eprint) Bioinformatics 25(19):2514-21 (2009)
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phyml
Phylogenetic estimation using Maximum Likelihood
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PhyML is a software that estimates maximum likelihood phylogenies from alignments of nucleotide or amino acid sequences. It provides a wide range of options that were designed to facilitate standard phylogenetic analyses. The main strengths of PhyML lies in the large number of substitution models coupled to various options to search the space of phylogenetic tree topologies, going from very fast and efficient methods to slower but generally more accurate approaches. It also implements two methods to evaluate branch supports in a sound statistical framework (the non-parametric bootstrap and the approximate likelihood ratio test).

PhyML was designed to process moderate to large data sets. In theory, alignments with up to 4,000 sequences 2,000,000 character-long can be analyzed. In practice however, the amount of memory required to process a data set is proportional of the product of the number of sequences by their length. Hence, a large number of sequences can only be processed provided that they are short. Also, PhyML can handle long sequences provided that they are not numerous. With most standard personal computers, the “comfort zone” for PhyML generally lies around 3 to 500 sequences less than 2,000 character long.

This package also includes PhyTime.

Please cite: Stéphane Guindon: Bayesian estimation of divergence times from large sequence alignments. (PubMed,eprint) Molecular Biology and Evolution 27(8):1768-81 (2010)
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phyutility
simple analyses or modifications on both phylogenetic trees and data matrices
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Phyutility (fyoo-til-i-te) is a command line program that performs simple analyses or modifications on both trees and data matrices.

Currently it performs the following functions (to suggest another feature, submit an Issue and use the label Type-Enhancement) :

Trees

  • rerooting
  • pruning
  • type conversion
  • consensus
  • leaf stability
  • lineage movement
  • tree support

Data Matrices

  • concatenate alignments
  • genbank parsing
  • trimming alignments
  • search NCBI
  • fetch NCBI
Please cite: Stephen A. Smith and Casey W. Dunn: Phyutility: a phyloinformatics utility for trees, alignments, and molecular data. (PubMed,eprint) Bioinformatics 24(5):715-716 (2008)
picard-tools
Command line tools to manipulate SAM and BAM files
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SAM (Sequence Alignment/Map) format is a generic format for storing large nucleotide sequence alignments. Picard Tools includes these utilities to manipulate SAM and BAM files:

 AddCommentsToBam                  FifoBuffer
 AddOrReplaceReadGroups            FilterSamReads
 BaitDesigner                      FilterVcf
 BamIndexStats                     FixMateInformation
                                   GatherBamFiles
 BedToIntervalList                 GatherVcfs
 BuildBamIndex                     GenotypeConcordance
 CalculateHsMetrics                IlluminaBasecallsToFastq
 CalculateReadGroupChecksum        IlluminaBasecallsToSam
 CheckIlluminaDirectory            LiftOverIntervalList
 CheckTerminatorBlock              LiftoverVcf
 CleanSam                          MakeSitesOnlyVcf
 CollectAlignmentSummaryMetrics    MarkDuplicates
 CollectBaseDistributionByCycle    MarkDuplicatesWithMateCigar
 CollectGcBiasMetrics              MarkIlluminaAdapters
 CollectHiSeqXPfFailMetrics        MeanQualityByCycle
 CollectIlluminaBasecallingMetrics MergeBamAlignment
 CollectIlluminaLaneMetrics        MergeSamFiles
 CollectInsertSizeMetrics          MergeVcfs
 CollectJumpingLibraryMetrics      NormalizeFasta
 CollectMultipleMetrics            PositionBasedDownsampleSam
 CollectOxoGMetrics                QualityScoreDistribution
 CollectQualityYieldMetrics        RenameSampleInVcf
 CollectRawWgsMetrics              ReorderSam
 CollectRnaSeqMetrics              ReplaceSamHeader
 CollectRrbsMetrics                RevertOriginalBaseQualitiesAndAddMateCigar
 CollectSequencingArtifactMetrics  RevertSam
 CollectTargetedPcrMetrics         SamFormatConverter
 CollectVariantCallingMetrics      SamToFastq
 CollectWgsMetrics                 ScatterIntervalsByNs
 CompareMetrics                    SortSam
 CompareSAMs                       SortVcf
 ConvertSequencingArtifactToOxoG   SplitSamByLibrary
 CreateSequenceDictionary          SplitVcfs
 DownsampleSam                     UpdateVcfSequenceDictionary
 EstimateLibraryComplexity         ValidateSamFile
 ExtractIlluminaBarcodes           VcfFormatConverter
 ExtractSequences                  VcfToIntervalList
 FastqToSam                        ViewSam
The package is enhanced by the following packages: multiqc
Please cite: Broad Institute: Picard toolkit. Broad Institute, GitHub repository (2019)
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Topics: Sequencing; Document, record and content management
plink
whole-genome association analysis toolset
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plink expects as input the data from SNP (single nucleotide polymorphism) chips of many individuals and their phenotypical description of a disease. It finds associations of single or pairs of DNA variations with a phenotype and can retrieve SNP annotation from an online source.

SNPs can evaluated individually or as pairs for their association with the disease phenotypes. The joint investigation of copy number variations is supported. A variety of statistical tests have been implemented.

Please note: The executable was renamed to plink1 because of a name clash. Please read more about this in /usr/share/doc/plink/README.Debian.

Please cite: Shaun Purcell, Benjamin Neale, Kathe Todd-Brown, Lori Thomas, Manuel A. R. Ferreira, David Bender, Julian Maller, Pamela Sklar, Paul I. W. de Bakker, Mark J. Daly and Pak C. Sham: PLINK: a toolset for whole-genome association and population-based linkage analysis. (PubMed) American Journal of Human Genetics 81(3):559-75 (2007)
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plink1.9
whole-genome association analysis toolset
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plink expects as input the data from SNP (single nucleotide polymorphism) chips of many individuals and their phenotypical description of a disease. It finds associations of single or pairs of DNA variations with a phenotype and can retrieve SNP annotation from an online source.

SNPs can evaluated individually or as pairs for their association with the disease phenotypes. The joint investigation of copy number variations is supported. A variety of statistical tests have been implemented.

plink1.9 is a comprehensive update of plink with new algorithms and new methods, faster and less memory consumer than the first plink.

Please note: The executable was renamed to plink1.9 because of a name clash. Please read more about this in /usr/share/doc/plink1.9/README.Debian.

Please cite: Christopher C. Chang, Carson C. Chow, Laurent C.A.M. Tellier, Shashaank Vattikuti, Shaun M. Purcell and James J. Lee: Second-generation PLINK: rising to the challenge of larger and richer datasets. (eprint) GigaScience 4(1):7 (2015)
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plink2
whole-genome association analysis toolset
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plink expects as input the data from SNP (single nucleotide polymorphism) chips of many individuals and their phenotypical description of a disease. It finds associations of single or pairs of DNA variations with a phenotype and can retrieve SNP annotation from an online source.

SNPs can evaluated individually or as pairs for their association with the disease phenotypes. The joint investigation of copy number variations is supported. A variety of statistical tests have been implemented.

plink2 is a comprehensive update of plink and plink1.9 with new algorithms and new methods, faster and less memory consumer than the first plink.

Please cite: Christopher C. Chang, Carson C. Chow, Laurent C.A.M. Tellier, Shashaank Vattikuti, Shaun M. Purcell and James J. Lee: Second-generation PLINK: rising to the challenge of larger and richer datasets. (eprint) GigaScience 4(1):7 (2015)
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poa
다중 서열 배치를 위한 부분 순서 배치
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POA는 부분 순서 배치(Partial Order Alignment)로 생물 정보학의 다중 서열 배 치 (MSA - Multiple Sequence Alignment)를 위한 빠른 프로그램입니다. POA의 장 점으로는 속도, 확장성, 감도, 그리고 정렬에서 분기 / 삽입-결실 처리에 대한 우수한 능력이 있습니다. 부분 순서 배치는 MSA에 대한 처리 방법이며, 그래서 진보적 배치처럼 기존의 방법과 결합될 수 있습니다. POA는 MSA 한 쌍을 최적으 로 정렬하며 그래서 클러스탈 같은 진보된 정렬 방법에 직접 적용될 수 있습니 다. 대량의 정렬을 위해, 진보적인 POA는 CLUSTALW에 비해 10-30배정도 빠릅니 다. POA는 생물 정보학에 게시되었습니다.

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prank
Probabilistic Alignment Kit for DNA, codon and amino-acid sequences
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PRANK is a probabilistic multiple alignment program for DNA, codon and amino-acid sequences. It's based on a novel algorithm that treats insertions correctly and avoids over-estimation of the number of deletion events. In addition, PRANK borrows ideas from maximum likelihood methods used in phylogenetics and correctly takes into account the evolutionary distances between sequences. Lastly, PRANK allows for defining a potential structure for sequences to be aligned and then, simultaneously with the alignment, predicts the locations of structural units in the sequences.

PRANK is a command-line program for UNIX-style environments but the same sequence alignment engine is implemented in the graphical program PRANKSTER. In addition to providing a user-friendly interface to those not familiar with Unix systems, PRANKSTER is an alignment browser for alignments saved in the HSAML format. The novel format allows for storing all the information generated by the aligner and the alignment browser is a convenient way to analyse and manipulate the data.

PRANK aims at an evolutionarily correct sequence alignment and often the result looks different from ones generated with other alignment methods. There are, however, cases where the different look is caused by violations of the method's assumptions. To understand why things may go wrong and how to avoid that, read this explanation of differences between PRANK and traditional progressive alignment methods.

Please cite: Ari Löztznoja: Phylogeny-aware alignment with PRANK. (PubMed) Methods Mol. Biol. 1079:155-170 (2014)
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prime-phylo
bayesian estimation of gene trees taking the species tree into account
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PrIME (Probabilistic Integrated Models of Evolution) is a package supporting inference of evolutionary parameters in a Bayesian framework using Markov chain Monte Carlo simulation. A distinguishing feature of PrIME is that the species tree is taken into account when analyzing gene trees.

The input data to PrIME is a multiple sequence alignment in FASTA format and the output data contains trees in Newick format.

Please cite: Ö. Åkerborg, B. Sennblad, L. Arvestad and J. Lagergren: Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. (PubMed,eprint) Proceedings of the National Academy of Sciences 106(14):5714-5719 (2009)
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primer3
tool to design flanking oligo nucleotides for DNA amplification
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Primer3 picks primers for Polymerase Chain Reactions (PCRs), considering as criteria oligonucleotide melting temperature, size, GC content and primer-dimer possibilities, PCR product size, positional constraints within the source sequence, and miscellaneous other constraints. All of these criteria are user-specifiable as constraints, and some are specifiable as terms in an objective function that characterizes an optimal primer pair.

Please cite: Steve Rozen and Helen J. Skaletsky: Primer3 on the WWW for general users and for biologist programmers. (PubMed,eprint) Methods Mol Biol. 132(3):365-86 (2000)
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probabel
Toolset for Genome-Wide Association Analysis
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The ProbABEL package is part of the GenABEL project for analysis of genome-wide data. ProbABEL is used to run GWAS. Using files in filevector/DatABEL format even allows for running GWAS on computers with only a few GB of RAM.

The package is enhanced by the following packages: probabel-examples
Please cite: Yurii S Aulchenko, Maksim V Struchalin and Cornelia M van Duijn: ProbABEL package for genome-wide association analysis of imputed data.. (PubMed,eprint) BMC Bioinformatics 11:134 (2010)
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probcons
PROBabilistic CONSistency-based multiple sequence alignment
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Tool for generating multiple alignments of protein sequences. Using a combination of probabilistic modeling and consistency-based alignment techniques, PROBCONS has achieved the highest accuracies of all alignment methods to date. On the BAliBASE benchmark alignment database, alignments produced by PROBCONS show statistically significant improvement over current programs, containing an average of 7% more correctly aligned columns than those of T-Coffee, 11% more correctly aligned columns than those of CLUSTAL W, and 14% more correctly aligned columns than those of DIALIGN.

Please cite: Chuong B. Do, Mahathi S.P. Mahabhashyam, Michael Brudno and Serafim Batzoglou: ProbCons: Probabilistic consistency-based multiple sequence alignment. (PubMed,eprint) Genome Research 15(2):330-340 (2005)
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proda
단백질 시퀀스의 다중 정열
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ProDA는 임의의 도메인 구조를 갖는 단백질 모임에서 상응하는 영역을 자동으로 감지 및 정렬하기 위한 시스템입니다. 정렬되지 않는 시퀀스 입력 집합이 주어지면, ProDA는 하나 이상의 시퀀스에 나타나는 모든 상응하는 지역을 식별하고, 그리고 이들 지역에 대한 내부 다중 정렬의 모음을 반환합니다.

Please cite: Tu Minh Phuong, Chuong B. Do, Robert C. Edgar and Serafim Batzoglou: Multiple alignment of protein sequences with repeats and rearrangements. (PubMed,eprint) Nucl. Acids Res. 34(20):5932-5942 (2006)
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prodigal
Microbial (bacterial and archaeal) gene finding program
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Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:

Speed: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.

Accuracy: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).

Specificity: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.

GC-Content Indifferent: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the Pseudomonas aeruginosa curated annotations.

Metagenomic Version: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.

Ease of Use: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.

Please cite: Doug Hyatt, Gwo-Liang Chen, Philip F. Locascio, Miriam L. Land, Frank W. Larimer and Loren J. Hauser: Prodigal: prokaryotic gene recognition and translation initiation site identification. (PubMed,eprint) BMC Bioinformatics 11:119 (2010)
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python3-biomaj3-cli
BioMAJ client
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BioMAJ downloads remote data banks, checks their status and applies transformation workflows, with consistent state, to provide ready-to-use data for biologists and bioinformaticians. For example, it can transform original FASTA files into BLAST indexes. It is very flexible and its post-processing facilities can be extended very easily.

BioMAJ3 is a rewrite of BioMAJ v1.x, see online documentation for migration.

This package contains the client to execute BioMAJ3 or communicate with the BioMAJ daemon process (python3-biomaj3-daemon) in case of microservice config.

python3-biopython
Python3 library for bioinformatics
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The Biopython Project is an international association of developers of freely available Python tools for computational molecular biology.

It is a distributed collaborative effort to develop Python3 libraries and applications which address the needs of current and future work in bioinformatics. The source code is made available under the Biopython License, which is extremely liberal and compatible with almost every license in the world. The project works along with the Open Bioinformatics Foundation, who generously provide web and CVS space for the project.

Please cite: Peter J. A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski and Michiel J. L. de Hoon: Biopython: freely available Python tools for computational molecular biology and bioinformatics. (PubMed,eprint) Bioinformatics 25(11):1422-1423 (2009)
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python3-cogent3
framework for genomic biology
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Newer upstream!
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PyCogent is a software library for genomic biology. It is a fully integrated and thoroughly tested framework for:

  • controlling third-party applications,
  • devising workflows; querying databases,
  • conducting novel probabilistic analyses of biological sequence evolution, and
  • generating publication quality graphics. It is distinguished by many unique built-in capabilities (such as true codon alignment) and the frequent addition of entirely new methods for the analysis of genomic data.
Please cite: Rob Knight, Peter Maxwell, Amanda Birmingham, Jason Carnes, J Gregory Caporaso, Brett C Easton, Michael Eaton, Micah Hamady, Helen Lindsay, Zongzhi Liu, Catherine Lozupone, Daniel McDonald, Michael Robeson, Raymond Sammut, Sandra Smit, Matthew J Wakefield, Jeremy Widmann, Shandy Wikman, Stephanie Wilson, Hua Ying and Gavin A Huttley: PyCogent: a toolkit for making sense from sequence. (PubMed,eprint) Genome Biology 8(8):R171 (2007)
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qiime
미생물 생태학에 대한 정량적 통찰력
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미생물은 인간, 동물, 식물 및 모든 기생충을 둘러싸고 있으며 이들과 이들이 살고 있는 환경에 강한 영향을 미칩니다. 토양의 질이 생각나지만 박테리아가 서로에게 미치는 영향도 생각해야 합니다. 인간은 항생제, 음식, 비료등을 통해 절대적이고 상대적인 풍부함에 영향을 미치고 있으며, 이러한 변화는 우리에게 영향을 미칩니다.

QIIME 2는 데이타와 분석 투명성에 포커싱을 맞춘 강력하고, 확장 가능하며, 분산된 미생물군유전체 분석 패키지입니다. QIIME 2는 연구자가 원시 DNA 염기서열 데이타로 분석을 시작하고 출판 품질 수치와 통계 결과로 마무리 할 수 있도록 합니다. 주요 특징들:

  • 데이타 출처의 통합 및 자동 추적
  • 시맨틱 유형 시스템
  • 미생물군유전체 분석 기능 확장을 위한 플러그인 시스템
  • 여러 유형의 사용자 인터페이스 지원 (예, API, 명령행, 그래픽)

QIIME2는 QIIME 1 미생물군유전체 분석 파이프라인을 완전히 새로 설계하고 새롭게 개발한 것 입니다. QIIME 2는 QIIME 1을 강력하고 널리 사용되는 분석 파이프라인으로 만든 기능들은 유지하면서 QIIME 1의 많은 제한 사항들을 해결합니다.

QIIME 2는 현재 초기 end-to-end 미생물군유전체 분석 파이프라인을 지원합니다. 새로운 기능은 QIIME 2 플러그인을 통해 정기적으로 제공됩니다. QIIME 2 플러그인 페이지에서 현재 사용가능한 플러그인 목록을 볼 수 있습니다. 향후에는 플러그인 페이지에서 개발중인 플러그인도 볼 수 있을 것 입니다.

Please cite: Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. (PubMed,eprint) Nature Biotechnology 37:852 - 857 (2019)
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Topics: Microbial ecology
r-bioc-edger
R의 디지털 유전자 발현 데이터에 대한 실증적 분석
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전체 전사체 시퀀싱 (RNA-seq)의 차등적 발현 분석과 생물학적 복제를 통한 디지털 유전자 발현 프로파일을 위한 생체전도체 패키지. 경험적 베이스 추정과 음이항 분포를 기반으로 한 정확한 검정을 사용합니다. 또한 다른 유형의 게놈 규모 카운트 데이터를 사용한 차등 신호 분석에도 유용합니다.

Please cite: Mark D. Robinson, Davis J. McCarthy and Gordon K. Smyth: edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. (PubMed,eprint) Bioinformatics 26,:139-140 (2010)
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r-bioc-hilbertvis
GNU R package to visualise long vector data
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This tool allows one to display very long data vectors in a space-efficient manner, by organising it along a 2D Hilbert curve. The user can then visually judge the large scale structure and distribution of features simultaenously with the rough shape and intensity of individual features.

In bioinformatics, a typical use case is ChIP-Chip and ChIP-Seq, or basically all the kinds of genomic data, that are conventionally displayed as quantitative track ("wiggle data") in genome browsers such as those provided by Ensembl or UCSC.

Please cite: Simon Anders: Visualization of genomic data with the Hilbert curve. (PubMed,eprint) Bioinformatics 25(10):1231-1235 (2009)
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r-cran-pvclust
Hierarchical Clustering with P-Values via Multiscale Bootstrap
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pvclust is a package for assessing the uncertainty in hierarchical cluster analysis. It provides AU (approximately unbiased) p-values as well as BP (boostrap probability) values computed via multiscale bootstrap resampling.

Please cite: Ryota Suzuki and Hidetoshi Shimodaira: Pvclust: an R package for assessing the uncertainty in hierarchical clustering. (PubMed,eprint) Bioinformatics 22(12):1540-1542 (2006)
r-cran-qtl
GNU R package for genetic marker linkage analysis
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R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org).

The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing.

A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses were implemented.

The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.

Please cite: Karl W. Broman, Hao Wu, Saunak Sen and Gary A. Churchill: R/qtl: QTL mapping in experimental crosses. (PubMed,eprint) Bioinformatics 19:889-890 (2003)
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r-cran-vegan
Community Ecology Package for R
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R package for community ecologists. It contains most multivariate analysis needed in analysing ecological communities, and tools for diversity analysis. Most diversity methods assume that data are counts of individuals.

These tools are sometimes used outside the field of ecology, for instance to study populations of white blood cells or RNA molecules.

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r-other-mott-happy.hbrem
GNU R package for fine-mapping complex diseases
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Happy is an R interface into the HAPPY C package for fine-mapping Quantitative Trait Loci (QTL) in Heterogenous Stocks (HS). An HS is an advanced intercross between (usually eight) founder inbred strains of mice. HS are suitable for fine-mapping QTL. It uses a multipoint analysis which offers significant improvements in statistical power to detect QTLs over that achieved by single-marker association.

The happy package is an extension of the original C program happy; it uses the C code to compute the probability of descent from each of the founders, at each locus position, but the happy packager allows a much richer range of models to be fit to the data.

Read /usr/share/doc/r-other-mott-happy/README.Debian for a more detailed explanation.

Please cite: Richard Mott, Christopher J. Talbot, Maria G. Turri, Allan C. Collins and Jonathan Flint: A method for fine mapping quantitative trait loci in outbred animal stocks. (PubMed,eprint) Proc. Natl. Acad. Sci. USA 97(23):12649-12654 (2000)
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raster3d
tools for generating images of proteins or other molecules
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Raster3D is a set of tools for generating high quality raster images of proteins or other molecules. The core program renders spheres, triangles, cylinders, and quadric surfaces with specular highlighting, Phong shading, and shadowing. It uses an efficient software Z-buffer algorithm which is independent of any graphics hardware. Ancillary programs process atomic coordinates from PDB files into rendering descriptions for pictures composed of ribbons, space-filling atoms, bonds, ball+stick, etc. Raster3D can also be used to render pictures composed in other programs such as Molscript in glorious 3D with highlights, shadowing, etc. Output is to pixel image files with 24 bits of color information per pixel.

Please cite: E.A. Merritt and D.J. Bacon: Raster3D Photorealistic Molecular Graphics. (PubMed) Methods in Enzymology 277:505-524 (1997)
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readseq
Conversion between sequence formats
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Reads and writes nucleic/protein sequences in various formats. Data files may have multiple sequences. Readseq is particularly useful as it automatically detects many sequence formats, and converts between them.

Please cite: Don Gilbert: Sequence file format conversion with command-line readseq. (PubMed,eprint) Current Protocols in Bioinformatics Appendix 1:E (2003)
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rnahybrid
Fast and effective prediction of microRNA/target duplexes
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RNAhybrid is a tool for finding the minimum free energy hybridisation of a long and a short RNA. The hybridisation is performed in a kind of domain mode, ie. The short sequence is hybridised to the best fitting part of the long one. The tool is primarily meant as a means for microRNA target prediction.

Please cite: Marc Rehmsmeier, Peter Steffen, Matthias Höchsmann and Robert Giegerich: Fast and effective prediction of microRNA/target duplexes. (PubMed,eprint) RNA 10(10):1507-1517 (2004)
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rtax
Classification of sequence reads of 16S ribosomal RNA gene
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Short-read technologies for microbial community profiling are increasingly popular, yet previous techniques for assigning taxonomy to paired-end reads perform poorly. RTAX provides rapid taxonomic assignments of paired-end reads using a consensus algorithm.

Please cite: David A. W. Soergel, Neelendu Dey, Rob Knight and Steven E. Brenner: Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences. (PubMed,eprint) The ISME Journal 6:1440–1444 (2012)
samtools
SAM, BAM, CRAM 형식에서 시퀀스 정렬 처리
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Samtools는 바이너리 BAM 형식으로 뉴클레오티드 시퀀스 정렬을 조작하는 유틸리티 세트입니다. ascii SAM (Sequence Alignment/Map) 및 CRAM 형식으로 가져오기 및 내보내기를 수행하고, 정렬, 병합, 인덱싱을 수행하며 모든 영역의 읽기를 신속하게 검색할 수 있습니다. 스트림상에서 작동하도록 설계되었으며 원격 FTP 또는 HTTP 서버에서 BAM 또는 CRAM (SAM 아님) 파일을 열 수 있습니다.

The package is enhanced by the following packages: libbio-samtools-perl multiqc
Please cite: Heng Li, Bob Handsaker, Alec Wysoker, Tim Fennell, Jue Ruan, Nils Homer, Gabor Marth, Goncalo Abecasis, Richard Durbin and 1000 Genome Project Data Processing Subgroup: The Sequence Alignment/Map (SAM) Format and SAMtools. (PubMed,eprint) Bioinformatics 25(16):2078-2079 (2009)
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seqan-apps
C++ library for the analysis of biological sequences
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SeqAn is a C++ template library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. This library applies a unique generic design that guarantees high performance, generality, extensibility, and integration with other libraries. SeqAn is easy to use and simplifies the development of new software tools with a minimal loss of performance. This package contains the applications dfi, pair_align, micro_razers, seqan_tcoffee, seqcons, razers and tree_recon.

Please cite: Andreas Doring, David Weese, Tobias Rausch and Knut Reinert: SeqAn An efficient, generic C++ library for sequence analysis. (PubMed,eprint) BMC Bioinformatics 9(1):11 (2008)
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sibsim4
align expressed RNA sequences on a DNA template
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The SIBsim4 project is based on sim4, which is a program designed to align an expressed DNA sequence with a genomic sequence, allowing for introns. SIBsim4 is a fairly extensive rewrite of the original code with the following goals:

  • speed improvement;
  • allow large, chromosome scale, DNA sequences to be used;
  • provide more detailed output about splice types;
  • provide more detailed output about polyA sites;
  • misc code cleanups and fixes.
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sigma-align
Simple greedy multiple alignment of non-coding DNA sequences
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Sigma (“Simple greedy multiple alignment”) is an alignment program. It's algorithm and scoring scheme are designed specifically for non-coding DNA sequence.

It uses a strategy of seeking the best possible gapless local alignments. This happens at each step making the best possible alignment consistent with existing alignments. It scores the significance of the alignment based on the lengths of the aligned fragments and a background model. These may be supplied or estimated from an auxiliary file of intergenic DNA.

Please cite: Siddharthan, Rahul: Sigma: multiple alignment of weakly-conserved non-coding DNA sequence. (PubMed) BMC Bioinformatics 7(1):143 (2006)
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sim4
tool for aligning cDNA and genomic DNA
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sim4 is a similarity-based tool for aligning an expressed DNA sequence (EST, cDNA, mRNA) with a genomic sequence for the gene. It also detects end matches when the two input sequences overlap at one end (i.e., the start of one sequence overlaps the end of the other).

sim4 employs a blast-based technique to first determine the basic matching blocks representing the "exon cores". In this first stage, it detects all possible exact matches of W-mers (i.e., DNA words of size W) between the two sequences and extends them to maximal scoring gap-free segments. In the second stage, the exon cores are extended into the adjacent as-yet-unmatched fragments using greedy alignment algorithms, and heuristics are used to favor configurations that conform to the splice-site recognition signals (GT-AG, CT-AC). If necessary, the process is repeated with less stringent parameters on the unmatched fragments.

Please cite: Liliana Florea, George Hartzell, Zheng Zhang, Gerald M. Rubin and Webb Miller: A Computer Program for Aligning a cDNA Sequence with a Genomic DNA Sequence. (PubMed,eprint) Genome Research 8:967-974 (1998)
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smalt
Sequence Mapping and Alignment Tool
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SMALT efficiently aligns DNA sequencing reads with a reference genome. Reads from a wide range of sequencing platforms, for example Illumina, Roche-454, Ion Torrent, PacBio or ABI-Sanger, can be processed including paired reads.

The software employs a perfect hash index of short words (< 20 nucleotides long), sampled at equidistant steps along the genomic reference sequences.

For each read, potentially matching segments in the reference are identified from seed matches in the index and subsequently aligned with the read using a banded Smith-Waterman algorithm.

The best gapped alignments of each read is reported including a score for the reliability of the best mapping. The user can adjust the trade-off between sensitivity and speed by tuning the length and spacing of the hashed words.

A mode for the detection of split (chimeric) reads is provided. Multi-threaded program execution is supported.

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snap
location of genes from DNA sequence with hidden markov model
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SNAP is a general purpose gene finding program suitable for both eukaryotic and prokaryotic genomes. SNAP is an acroynm for Semi-HMM-based Nucleic Acid Parser.

Please cite: Ian Korf: Gene finding in novel Genomes. (PubMed,eprint) BMC Bioinformatics 5:59 (2004)
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soapdenovo
short-read assembly method to build de novo draft assembly
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SOAPdenovo is a novel short-read assembly method that can build a de novo draft assembly for the human-sized genomes. The program is specially designed to assemble Illumina GA short reads.

It creates new opportunities for building reference sequences and carrying out accurate analyses of unexplored genomes in a cost effective way.

This version is not maintained anymore, consider using soapdenovo2.

Please cite: Ruiqiang Li, Hongmei Zhu, Jue Ruan, Wubin Qian, Xiaodong Fang, Zhongbin Shi, Yingrui Li, Shengting Li, Gao Shan, Karsten Kristiansen, Songgang Li, Huanming Yang, Jian Wang and Jun Wang: De novo assembly of human genomes with massively parallel short read sequencing. (PubMed,eprint) Genome Research 20(2):265-72 (2009)
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soapdenovo2
short-read assembly method to build de novo draft assembly
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SOAPdenovo is a novel short-read assembly method that can build a de novo draft assembly for the human-sized genomes. The program is specially designed to assemble Illumina GA short reads.

It creates new opportunities for building reference sequences and carrying out accurate analyses of unexplored genomes in a cost effective way.

Please cite: Ruibang Luo, Binghang Liu, Yinlong Xie, Zhenyu Li, Weihua Huang, Jianying Yuan, Guangzhu He, Yanxiang Chen, Qi Pan, Yunjie Liu, Jingbo Tang, Gengxiong Wu, Hao Zhang, Yujian Shi, Yong Liu, Chang Yu, Bo Wang, Yao Lu, Changlei Han, David W Cheung, Siu-Ming Yiu, Shaoliang Peng, Zhu Xiaoqian, Guangming Liu, Xiangke Liao, Yingrui Li, Huanming Yang, Jian Wang, Tak-Wah Lam and Jun Wang: SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Giga Science 1(1):18 (2012)
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squizz
Converter for genetic sequences and alignments
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Squizz is a sequence/alignment format checker, but it has some conversion capabilities too. Most common sequence and alignment formats are supported :

  • EMBL, FASTA, GCG, GDE, GENBANK, IG, NBRF, PIR (codata), RAW, and SWISSPROT.
  • CLUSTAL, FASTA, MEGA, MSF, NEXUS, PHYLIP (interleaved and sequential) and STOCKHOLM.
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sra-toolkit
utilities for the NCBI Sequence Read Archive
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Tools for reading the SRA archive, generally by converting individual runs into some commonly used format such as fastq.

The textual dumpers "sra-dump" and "vdb-dump" are provided in this release as an aid in visual inspection. It is likely that their actual output formatting will be changed in the near future to a stricter, more formalized representation[s]. PLEASE DO NOT RELY UPON THE OUTPUT FORMAT SEEN IN THIS RELEASE.

Other tools distributed in this package are:

 abi-dump, abi-load
 align-info
 bam-load
 cache-mgr
 cg-load
 copycat
 fasterq-dump
 fastq-dump, fastq-load
 helicos-load
 illumina-dump, illumina-load
 kar
 kdbmeta
 latf-load
 pacbio-load
 prefetch
 rcexplain
 remote-fuser
 sff-dump, sff-load
 sra-pileup, sra-sort, sra-stat, srapath
 srf-load
 test-sra
 vdb-config, vdb-copy, vdb-decrypt, vdb-encrypt, vdb-get, vdb-lock,
 vdb-passwd, vdb-unlock, vdb-validate

The "help" information will be improved in near future releases, and the tool options will become standardized across the set. More documentation will also be provided documentation on the NCBI web site.

Tool options may change in the next release. Version 1 tool options will remain supported wherever possible in order to preserve operation of any existing scripts.

Please cite: Rasko Leinonen, Ruth Akhtar, Ewan Birney, James Bonfield, Lawrence Bower, Matt Corbett, Ying Cheng, Fehmi Demiralp, Nadeem Faruque, Neil Goodgame, Richard Gibson, Gemma Hoad, Christopher Hunter, Mikyung Jang, Steven Leonard, Quan Lin, Rodrigo Lopez, Michael Maguire, Hamish McWilliam, Sheila Plaister, Rajesh Radhakrishnan, Siamak Sobhany, Guy Slater, Petra Ten Hoopen, Franck Valentin, Robert Vaughan, Vadim Zalunin, Daniel Zerbino and Guy Cochrane: Improvements to services at the European Nucleotide Archive. (PubMed,eprint) Nucleic Acids Research 38(Database issue):D39-45 (2010)
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ssake
genomics application for assembling millions of very short DNA sequences
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The Short Sequence Assembly by K-mer search and 3′ read Extension (SSAKE) is a genomics application for aggressively assembling millions of short nucleotide sequences by progressively searching for perfect 3′-most k-mers using a DNA prefix tree. SSAKE is designed to help leverage the information from short sequences reads by stringently clustering them into contigs that can be used to characterize novel sequencing targets.

Please cite: Rene L. Warren, Granger G. Sutton, Steven J. M. Jones and Robert A. Holt: Assembling millions of short DNA sequences using SSAKE. (PubMed,eprint) Bioinformatics 23(4):500-501 (2007)
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Topics: Sequence assembly
staden-io-lib-utils
programs for manipulating DNA sequencing files
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The io_lib from the Staden package is a library of file reading and writing code to provide a general purpose trace file (and Experiment File) reading interface. It has been compiled and tested on a variety of unix systems, MacOS X and MS Windows.

This package contains the programs that are distributed with the Staden io_lib for manipulating and converting sequencing data files, and in particular files to manipulate short reads generated by second and third generation sequencers and stored in SRF format.

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t-coffee
Multiple Sequence Alignment
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T-Coffee is a multiple sequence alignment package. Given a set of sequences (Proteins or DNA), T-Coffee generates a multiple sequence alignment. Version 2.00 and higher can mix sequences and structures.

T-Coffee allows the combination of a collection of multiple/pairwise, global or local alignments into a single model. It can also estimate the level of consistency of each position within the new alignment with the rest of the alignments. See the pre-print for more information

T-Coffee has a special called M-Coffee that makes it possible to combine the output of many multiple sequence alignment packages. In its published version, it uses MUSCLE, PROBCONS, POA, DiAlign-TS, MAFFT, Clustal W, PCMA and T-Coffee. A special version has been made for Debian, DM-Coffee, that uses only free software by replacing Clustal W by Kalign. Using the 8 Methods of M-Coffee can sometimes be a bit heavy. You can use a subset of your favorite methods if you prefer.

The package is enhanced by the following packages: clustalw dialign-tx kalign mafft muscle muscle3 ncbi-blast+ poa prank probcons tm-align
Please cite: Cédric Notredame, Desmond G. Higgins and Jaap Heringa: T-coffee: a novel method for fast and accurate multiple sequence alignment. (PubMed) Journal of Molecular Biology 302(1):205-217 (2000)
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tabix
TAB으로 구분된 게놈 위치 파일용 일반 인덱서
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Tabix는 일부 컬럼이 시퀀스 좌표를 가르키는 파일을 인덱싱합니다: 이름 (일반적으로 염색체), 시작 및 중지. 입력 데이타 파일은 gzip과 유사한 인터페이스를 가지는 bgzip (이 패키지에서 제공)에 의해 위치 정렬 및 압축되어야 합니다. 인덱싱후, tabix는 염색체 좌표로 데이타 라인을 빠르게 검색할 수 있습니다. 빠른 데이타 검색은 URI가 파일 이름으로 제공되는 경우 네트워크에서도 작동합니다.

이 패키지는 HTSlib 소스에서 빌드되었으며, bgzip, htsfile, tabix 도구를 제공합니다.

Please cite: Heng Li: Tabix: fast retrieval of sequence features from generic TAB-delimited files. (PubMed,eprint) Bioinformatics 27(5):718-719 (2011)
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theseus
superimpose macromolecules using maximum likelihood
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Theseus is a program that simultaneously superimposes multiple macromolecular structures. Theseus finds the optimal solution to the superposition problem using the method of maximum likelihood. By down-weighting variable regions of the superposition and by correcting for correlations among atoms, the ML superposition method produces very accurate structural alignments.

When macromolecules with different residue sequences are superimposed, other programs and algorithms discard residues that are aligned with gaps. Theseus, however, uses a novel superimposition algorithm that includes all of the data.

The package is enhanced by the following packages: theseus-examples
Please cite: Douglas L. Theobald and Deborah S. Wuttke: THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures. (eprint) Bioinformatics 22(17):2171-2172 (2006)
tigr-glimmer
Gene detection in archea and bacteria
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Developed by the TIGR institute this software detects coding sequences in bacteria and archea.

Glimmer is a system for finding genes in microbial DNA, especially the genomes of bacteria and archaea. Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DNA.

Please cite: Steven L. Salzberg, Arthur L. Delcher, S. Kasif and O. White: Microbial gene identification using interpolated Markov models. (PubMed,eprint) Nucleic Acids Research 26(2):544-8 (1998)
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tree-ppuzzle
최대 가능성에 의한 계통 발생 수의 병렬 재구성
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TREE-PUZZLE (PUZZLE의 새로운 이름)은 대규모 데이터 세트를 분석하고 각 내부 분기에 대한 지원 추정치를 자동으로 할당하는, 빠른 트리 검색 알고리즘, quartet puzzling을 구현하는 대화형 콘솔입니다. TREE-PUZZLE은 또한 사용자가 지정한 트리에 대한 브렌치 길이뿐만 아니라 쌍별 최대 우도 거리도 계산합니다. 브렌치 길이는 클록 가정에 따라 계산될 수도 있습니다. 또한 TREE-PUZZLE은 전체 트리를 계산하지 않고 가정된 내부 브렌치의 지원을 조사하고 서열 정렬의 계통발생적 내용을 시각화하기 위해 새로운 방법인, 우도 매핑을 제공합니다.

Please cite: Heiko A. Schmidt, Korbinian Strimmer, Martin Vingron and Arndt von Haeseler: TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. (PubMed,eprint) Bioinformatics 18(3):502-504 (2002)
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tree-puzzle
Reconstruction of phylogenetic trees by maximum likelihood
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TREE-PUZZLE (the new name for PUZZLE) is an interactive console program that implements a fast tree search algorithm, quartet puzzling, that allows analysis of large data sets and automatically assigns estimations of support to each internal branch. TREE-PUZZLE also computes pairwise maximum likelihood distances as well as branch lengths for user specified trees. Branch lengths can also be calculated under the clock-assumption. In addition, TREE-PUZZLE offers a novel method, likelihood mapping, to investigate the support of a hypothesized internal branch without computing an overall tree and to visualize the phylogenetic content of a sequence alignment.

Please cite: Heiko A. Schmidt, Korbinian Strimmer, Martin Vingron and Arndt von Haeseler: TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. (PubMed,eprint) Bioinformatics 18(3):502-504 (2002)
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vcftools
VCF 파일 작업을 위한 도구 모음
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VCFtools는 1000 게놈 프로젝트에 의해서 생성된 것과 같은 VCF 파일 작업을 위 해 디자인된 프로그램 패키지입니다. VCFtools의 목적은 VCF 파일 작업을 위한 방법을 제공하는 것 입니다: 몇가지 기본적인 인구 유전 통계를 검증, 병합, 비 교, 계산합니다.

The package is enhanced by the following packages: multiqc
Please cite: Petr Danecek, Adam Auton, Goncalo Abecasis, Cornelis A. Albers, Eric Banks, Mark A. DePristo, Robert E. Handsaker, Gerton Lunter, Gabor T. Marth, Stephen T. Sherry, Gilean McVean and Richard Durbin: The variant call format and VCFtools. (PubMed,eprint) Bioinformatics 27(15):2156-8 (2011)
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velvet
Nucleic acid sequence assembler for very short reads
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Velvet is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454, developed by Daniel Zerbino and Ewan Birney at the European Bioinformatics Institute (EMBL-EBI), near Cambridge, in the United Kingdom.

Velvet currently takes in short read sequences, removes errors then produces high quality unique contigs. It then uses paired read information, if available, to retrieve the repeated areas between contigs.

Please cite: Daniel R. Zerbino and Ewan Birney: Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. (PubMed,eprint) Genome Research 18(5):821-829 (2008)
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veryfasttree
Speeding up the estimation of phylogenetic trees from sequences
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VeryFastTree is a highly efficient implementation inspired by the FastTree-2 tool, designed to expedite the inference of approximately-maximum-likelihood phylogenetic trees from nucleotide or protein sequence alignments. It is an optimized implementation designed to accelerate the estimation of phylogenies for large alignments. By leveraging parallelization and vectorization strategies, VeryFastTree significantly improves the performance and scalability of phylogenetic analysis, allowing it to construct phylogenetic trees in a fraction of the time previously required.

Maintaining the integrity of FastTree-2, VeryFastTree retains the same phases, methods, and heuristics used for estimating phylogenetic trees. This ensures that the topological accuracy of the trees produced by VeryFastTree remains equivalent to that of FastTree-2. Moreover, unlike the parallel version of FastTree-2, VeryFastTree guarantees deterministic results, eliminating any potential variations in the output.

To facilitate a seamless transition for users, VeryFastTree adopts the exact same command line arguments as FastTree-2. This means that by simply substituting FastTree-2 with VeryFastTree, and using the same set of options, users can significantly enhance the overall performance of their phylogenetic analyses.

wise
comparison of biopolymers, like DNA and protein sequences
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Wise2 is a package focused on comparisons of biopolymers, commonly DNA and protein sequences. There are many other packages which do this, probably the best known being BLAST package (from NCBI) and the Fasta package (from Bill Pearson). There are other packages, such as the HMMER package (Sean Eddy) or SAM package (UC Santa Cruz) focused on hidden Markov models (HMMs) of biopolymers.

Wise2's particular forte is the comparison of DNA sequence at the level of its protein translation. This comparison allows the simultaneous prediction of say gene structure with homology based alignment.

Wise2 also contains other algorithms, such as the venerable Smith-Waterman algorithm, or more modern ones such as Stephen Altschul's generalised gap penalties, or even experimental ones developed in house, such as dba. The development of these algorithms is due to the ease of developing such algorithms in the environment used by Wise2.

Wise2 has also been written with an eye for reuse and maintainability. Although it is a pure C package you can access its functionality directly in Perl. Parts of the package (or the entire package) can be used by other C or C++ programs without namespace clashes as all externally linked variables have the unique identifier Wise2 prepended.

Please cite: Ewan Birney, Michele Clamp and Richard Durbin: GeneWise and Genomewise. (PubMed,eprint) Genome Research 14(5):988-95 (2004)
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cufflinks
Transcript assembly, differential expression and regulation for RNA-Seq
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Cufflinks assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one.

This package provides the binary of cufflinks and associated tools, i.e. compress_gtf, cuffcompare, cuffdiff, cuffmerge, cuffnorm, cuffquant and gtf_to_sam.

Please cite: Cole Trapnell, Brian A Williams, Geo Pertea, Ali Mortazavi, Gordon Kwan, Marijke J van Baren, Steven L Salzberg, Barbara J Wold and Lior Pachter: Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. (PubMed) Nature Biotechnology 28(5):511-515 (2010)
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embassy-phylip
EMBOSS conversions of the programs in the phylip package
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This package is the adaptation of the PHYLIP package in which its programs can operate with the biological sequence formats and databases of the European Molecular Biology Open Software Suite (EMBOSS). The software packages adapted for EMBOSS are called EMBASSY.

PHYLIP (the PHYLogeny Inference Package) is a package of programs for inferring phylogenies (evolutionary trees). Methods that are available in the package include parsimony, distance matrix, and likelihood methods, including bootstrapping and consensus trees. Data types that can be handled include molecular sequences, gene frequencies, restriction sites and fragments, distance matrices, and discrete characters.

The EMBASSY PHYLIP programs all have the prefix "f" to distinguish them from the original programs and avoid namespace conflict.

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bagpipe
genomewide LD mapping
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Bagpipe is a program for performing genomewide linkage disequilibrium mapping of quantitative trait loci in populations whose genome structure can be accommodated in the HAPPY framework [Mott00]. This includes most diploid crosses where the founders of the individuals have known genotypes.

  • Bagpipe is a simplified and streamlined version of Bagphenotype that does not currently include resample model averaging (RMA) capabilities.
  • Bagpipe can help fit single locus regression models (with or without random effects) to marker intervals whose genetic ancestry is inferred using the HAPPY software.
  • Bagpipe cannot help you decide what is a sensible model to fit.
  • Bagpipe does not currently accommodate populations with significant population structure, except through the specification of simple random intercepts based on unpatterned covariance matrices.
  • Bagpipe is named after the Scottish wind instrument "the bagpipes" and after Bagphenotype, which in turn was a PIPEline for BAGging-based multiple QTL analysis of phenoTYPEs. Bagphenotype was in turn based on software written by Richard Mott and William Valdar to analyze heterogeneous stock mice in [Valdar06].
  • Bagpipe is experimental software, is provided free of charge subject to copyleft restrictions, and comes with no guarantees whatsoever.
Please cite: Richard Mott, Christopher J. Talbot, Maria G. Turri, Allan C. Collins and Jonathan Flint: A method for fine mapping quantitative trait loci in outbred animal stocks. (PubMed) Proc Natl Acad Sci U S A. 97(23):12649-54 (200)
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