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authorMădălin Ionel Patrașcu <madalinionel.patrascu@mdc-berlin.de>2022-06-19 22:42:01 +0200
committerRicardo Wurmus <rekado@elephly.net>2022-11-24 18:02:15 +0100
commit8d3bd8e4b08fef0ea7fac48296191d3e6e342e9c (patch)
treec5fa5771971e241d385d4565cd3a15e9b3660630
parenta8c36bf8c49d1f790d4132a47e95972bba793c89 (diff)
downloadguix-8d3bd8e4b08fef0ea7fac48296191d3e6e342e9c.tar
guix-8d3bd8e4b08fef0ea7fac48296191d3e6e342e9c.tar.gz
gnu: Add r-ancombc.
* gnu/packages/bioconductor.scm (r-ancombc): New variable.
-rw-r--r--gnu/packages/bioconductor.scm46
1 files changed, 46 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index 61f312e17f..d9303b5873 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -2284,6 +2284,52 @@ of Medical Research. The goal is to provide a standard library for quantitative
analysis, modelling, and visualization of spike-in controls.")
(license license:bsd-3)))
+(define-public r-ancombc
+ (package
+ (name "r-ancombc")
+ (version "1.6.1")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "ANCOMBC" version))
+ (sha256
+ (base32
+ "1p9yryv85qk7m3hbflmpdffd3azpsifcw54x1rp8sb67yjmq3whq"))))
+ (properties `((upstream-name . "ANCOMBC")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-desctools
+ r-doparallel
+ r-dorng
+ r-dplyr
+ r-energy
+ r-foreach
+ r-hmisc
+ r-magrittr
+ r-mass
+ r-microbiome
+ r-nlme
+ r-nloptr
+ r-phyloseq
+ r-rdpack
+ r-rlang
+ r-tibble
+ r-tidyr))
+ (native-inputs (list r-knitr))
+ (home-page "https://github.com/FrederickHuangLin/ANCOMBC")
+ (synopsis "Analysis of compositions of microbiomes with bias correction")
+ (description
+ "@code{ANCOMBC} is a package containing @dfn{differential abundance} (DA)
+and correlation analyses for microbiome data. Specifically, the package
+includes @dfn{Analysis of Compositions of Microbiomes with Bias
+Correction}(ANCOM-BC) and @dfn{Analysis of Composition of Microbiomes} (ANCOM)
+for DA analysis, and @dfn{Sparse Estimation of Correlations among
+Microbiomes} (SECOM) for correlation analysis. Microbiome data are typically
+subject to two sources of biases: unequal sampling fractions (sample-specific
+biases) and differential sequencing efficiencies (taxon-specific biases).
+Methodologies included in the @code{ANCOMBC} package were designed to correct
+these biases and construct statistically consistent estimators.")
+ (license license:artistic2.0)))
+
(define-public r-aldex2
(package
(name "r-aldex2")