gnu: Add r-multtest.
* gnu/packages/bioconductor.scm (r-multtest): New variable.
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@ -147,3 +147,41 @@ a suite of bioinformatics tools integrated within this self-contained software
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package comprehensively addressing issues ranging from post-alignments
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package comprehensively addressing issues ranging from post-alignments
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processing to visualization and annotation.")
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processing to visualization and annotation.")
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(license license:gpl2)))
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(license license:gpl2)))
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(define-public r-multtest
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(package
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(name "r-multtest")
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(version "2.34.0")
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(source
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(origin
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(method url-fetch)
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(uri (bioconductor-uri "multtest" version))
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(sha256
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(base32
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"0n11rd49xl2vn3ldmfips7d3yb70l8npjcqsxyswr9ypjhgzkv9j"))))
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(build-system r-build-system)
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(propagated-inputs
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`(("r-survival" ,r-survival)
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("r-biocgenerics" ,r-biocgenerics)
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("r-biobase" ,r-biobase)
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("r-mass" ,r-mass)))
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(home-page "http://bioconductor.org/packages/multtest")
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(synopsis "Resampling-based multiple hypothesis testing")
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(description
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"This package can do non-parametric bootstrap and permutation
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resampling-based multiple testing procedures (including empirical Bayes
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methods) for controlling the family-wise error rate (FWER), generalized
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family-wise error rate (gFWER), tail probability of the proportion of
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false positives (TPPFP), and false discovery rate (FDR). Several choices
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of bootstrap-based null distribution are implemented (centered, centered
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and scaled, quantile-transformed). Single-step and step-wise methods are
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available. Tests based on a variety of T- and F-statistics (including
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T-statistics based on regression parameters from linear and survival models
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as well as those based on correlation parameters) are included. When probing
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hypotheses with T-statistics, users may also select a potentially faster null
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distribution which is multivariate normal with mean zero and variance
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covariance matrix derived from the vector influence function. Results are
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reported in terms of adjusted P-values, confidence regions and test statistic
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cutoffs. The procedures are directly applicable to identifying differentially
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expressed genes in DNA microarray experiments.")
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(license license:lgpl3)))
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