diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index 45711ab6b6..251ad1e1ac 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -2424,3 +2424,62 @@ variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays.") (license license:lgpl2.0+))) + +(define-public r-linnorm + (package + (name "r-linnorm") + (version "2.6.1") + (source + (origin + (method url-fetch) + (uri (bioconductor-uri "Linnorm" version)) + (sha256 + (base32 + "1qgk8m5kc409flqxs3vnf228v3z0112q8py9hgfgyiwvi6yzdbp6")))) + (properties `((upstream-name . "Linnorm"))) + (build-system r-build-system) + (propagated-inputs + `(("r-amap" ,r-amap) + ("r-apcluster" ,r-apcluster) + ("r-ellipse" ,r-ellipse) + ("r-fastcluster" ,r-fastcluster) + ("r-fpc" ,r-fpc) + ("r-ggdendro" ,r-ggdendro) + ("r-ggplot2" ,r-ggplot2) + ("r-gmodels" ,r-gmodels) + ("r-igraph" ,r-igraph) + ("r-limma" ,r-limma) + ("r-mass" ,r-mass) + ("r-mclust" ,r-mclust) + ("r-rcpp" ,r-rcpp) + ("r-rcpparmadillo" ,r-rcpparmadillo) + ("r-rtsne" ,r-rtsne) + ("r-statmod" ,r-statmod) + ("r-vegan" ,r-vegan) + ("r-zoo" ,r-zoo))) + (home-page "http://www.jjwanglab.org/Linnorm/") + (synopsis "Linear model and normality based transformation method") + (description + "Linnorm is an R package for the analysis of RNA-seq, scRNA-seq, ChIP-seq +count data or any large scale count data. It transforms such datasets for +parametric tests. In addition to the transformtion function (@code{Linnorm}), +the following pipelines are implemented: + +@enumerate +@item Library size/batch effect normalization (@code{Linnorm.Norm}) +@item Cell subpopluation analysis and visualization using t-SNE or PCA K-means + clustering or hierarchical clustering (@code{Linnorm.tSNE}, + @code{Linnorm.PCA}, @code{Linnorm.HClust}) +@item Differential expression analysis or differential peak detection using + limma (@code{Linnorm.limma}) +@item Highly variable gene discovery and visualization (@code{Linnorm.HVar}) +@item Gene correlation network analysis and visualization (@code{Linnorm.Cor}) +@item Stable gene selection for scRNA-seq data; for users without or who do + not want to rely on spike-in genes (@code{Linnorm.SGenes}) +@item Data imputation (@code{Linnorm.DataImput}). +@end enumerate + +Linnorm can work with raw count, CPM, RPKM, FPKM and TPM. Additionally, the +@code{RnaXSim} function is included for simulating RNA-seq data for the +evaluation of DEG analysis methods.") + (license license:expat)))