gnu: Add r-linnorm.

* gnu/packages/bioconductor.scm (r-linnorm): New variable.
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Ricardo Wurmus 2019-03-13 17:13:21 +01:00
parent 70daf82f28
commit 4291f36a22
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@ -2424,3 +2424,62 @@ (define-public r-lumi
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)))