Debian Med Project
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Summary
Statistics
Debian Med statistics

This metapackage will install packages which are helpful to do statistics with a special focus on tasks in medical care.

Description

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

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

Links to other tasks

Debian Med Statistics packages

Official Debian packages with high relevance

r-bioc-edger
Empirical analysis of digital gene expression data in R
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Bioconductor package for differential expression analysis of whole transcriptome sequencing (RNA-seq) and digital gene expression profiles with biological replication. It uses empirical Bayes estimation and exact tests based on the negative binomial distribution. It is also useful for differential signal analysis with other types of genome-scale count data.

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-limma
linear models for microarray data
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Microarrays are microscopic plates with carefully arranged short DNA strands and/or chemically prepared surfaces to which other DNA preferably binds. The amount of DNA binding at different locations of these chips, typically determined by a fluorescent dye, is to be interpreted. The technology is typically used with DNA that is derived from RNA, i.e to determine the activity of a gene and/or its splice variants. But the technology is also used to determine sequence variations in genomic DNA.

This Bioconductor package supports the analysis of gene expression microarray data, especially the use of linear models for analysing designed experiments and the assessment of differential expression. The package includes pre-processing capabilities for two-colour spotted arrays. The differential expression methods apply to all array platforms and treat Affymetrix, single channel and two channel experiments in a unified way.

Please cite: Gordon K. Smyth: Limma: linear models for microarray data. (eprint) :397-420 (2005)
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r-bioc-multtest
Bioconductor resampling-based multiple hypothesis testing
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Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.

r-bioc-qvalue
GNU R package for Q-value estimation for FDR control
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This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.

Please cite: John D Storey and Robert Tibshirani: Statistical significance for genomewide studies. (PubMed,eprint) Proceedings of the National Academy of Sciences of the United States of America 100(16):9440-9445 (2003)
r-cran-ade4
GNU R analysis of ecological data
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This GNU R package allows analysis of ecological data and contains exploratory and euclidean methods in environmental sciences.

It supports multivariate data analysis and graphical display.

Please cite: Stéphane Dray and Anne-Béatrice Dufour: The ade4 Package: Implementing the Duality Diagram for Ecologists. (eprint) Journal of Statistical Software 22(4):1-20 (2007)
r-cran-beeswarm
bee swarm plot, an alternative to stripchart
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Beeswarm is an add-on package for the R statistical environment. The bee swarm plot is a one-dimensional scatter plot like "stripchart", but with closely-packed, non-overlapping points.

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-randomforest
GNU R package implementing the random forest classificator
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RandomForest implements Breiman’s random forest algorithm (based on Breiman and Cutler’s original Fortran code) for classification and regression. It can also be used in unsupervised mode for assessing proximities among data points.

The technique uses multiple decision trees and combines their individual votes.

r-cran-rwave
GNU R time-frequency analysis of 1-D signals
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A set of R functions which provide an environment for the Time-Frequency analysis of 1-D signals (and especially for the wavelet and Gabor transforms of noisy signals). It was originally written for Splus by Rene Carmona, Bruno Torresani, and Wen L. Hwang, first at the University of California at Irvine and then at Princeton University. Credit should also be given to Andrea Wang whose functions on the dyadic wavelet transform are included. Rwave is based on the book: "Practical Time-Frequency Analysis: Gabor and Wavelet Transforms with an Implementation in S", by Rene Carmona, Wen L. Hwang and Bruno Torresani (1998, eBook ISBN:978008053942), Academic Press.

r-cran-snowfall
GNU R easier cluster computing (based on snow)
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Usability wrapper around snow for easier development of parallel R programs. This package offers e.g. extended error checks, and additional functions. All functions work in sequential mode, too, if no cluster is present or wished. Package is also designed as connector to the cluster management tool sfCluster, but can also used without it.

r-cran-waveslim
GNU R wavelet routines for 1-, 2- and 3-D signal processing
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Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.

r-cran-wavethresh
GNU R wavelets statistics and transforms
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Performs 1, 2 and 3D real and complex-valued wavelet transforms, nondecimated transforms, wavelet packet transforms, nondecimated wavelet packet transforms, multiple wavelet transforms, complex-valued wavelet transforms, wavelet shrinkage for various kinds of data, locally stationary wavelet time series, nonstationary multiscale transfer function modeling, density estimation.

Official Debian packages with lower relevance

science-statistics
Debian Science Statistics packages
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This metapackage is part of the Debian Pure Blend "Debian Science" and installs packages related to statistics. This task is a general task which might be useful for any scientific work. It depends from a lot of R packages as well as from other tools which are useful to do statistics. Moreover the Science Mathematics task is suggested to optionally install all mathematics related software.

Packaging has started and developers might try the packaging code in VCS

rstudio
GNU R IDE
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Version: 2022.07.1+554-1

RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.

*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 237401