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author | Mădălin Ionel Patrașcu <madalinionel.patrascu@mdc-berlin.de> | 2022-06-19 22:42:01 +0200 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2022-11-24 18:02:15 +0100 |
commit | 8d3bd8e4b08fef0ea7fac48296191d3e6e342e9c (patch) | |
tree | c5fa5771971e241d385d4565cd3a15e9b3660630 /gnu/packages/bioconductor.scm | |
parent | a8c36bf8c49d1f790d4132a47e95972bba793c89 (diff) |
gnu: Add r-ancombc.
* gnu/packages/bioconductor.scm (r-ancombc): New variable.
Diffstat (limited to 'gnu/packages/bioconductor.scm')
-rw-r--r-- | gnu/packages/bioconductor.scm | 46 |
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") |