;;; GNU Guix --- Functional package management for GNU ;;; Copyright © 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 Ricardo Wurmus ;;; Copyright © 2016, 2017, 2018, 2020, 2021 Roel Janssen ;;; Copyright © 2016 Pjotr Prins ;;; Copyright © 2016 Ben Woodcroft ;;; Copyright © 2017 Efraim Flashner ;;; Copyright © 2017, 2018, 2019, 2020, 2021 Tobias Geerinckx-Rice ;;; Copyright © 2019, 2020, 2021, 2022 Simon Tournier ;;; Copyright © 2020 Peter Lo ;;; Copyright © 2020, 2021, 2022 Mădălin Ionel Patrașcu ;;; Copyright © 2020 Jakub Kądziołka ;;; Copyright © 2021 Hong Li ;;; Copyright © 2021 Tim Howes ;;; Copyright © 2021 Nicolas Vallet ;;; ;;; This file is part of GNU Guix. ;;; ;;; GNU Guix is free software; you can redistribute it and/or modify it ;;; under the terms of the GNU General Public License as published by ;;; the Free Software Foundation; either version 3 of the License, or (at ;;; your option) any later version. ;;; ;;; GNU Guix is distributed in the hope that it will be useful, but ;;; WITHOUT ANY WARRANTY; without even the implied warranty of ;;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ;;; GNU General Public License for more details. ;;; ;;; You should have received a copy of the GNU General Public License ;;; along with GNU Guix. If not, see . (define-module (gnu packages bioconductor) #:use-module ((guix licenses) #:prefix license:) #:use-module (guix packages) #:use-module (guix download) #:use-module (guix git-download) #:use-module (guix build-system r) #:use-module (gnu packages) #:use-module (gnu packages base) #:use-module (gnu packages bioinformatics) #:use-module (gnu packages boost) #:use-module (gnu packages cran) #:use-module (gnu packages compression) #:use-module (gnu packages curl) #:use-module (gnu packages docker) #:use-module (gnu packages gcc) #:use-module (gnu packages graph) #:use-module (gnu packages graphviz) #:use-module (gnu packages haskell-xyz) #:use-module (gnu packages image) #:use-module (gnu packages maths) #:use-module (gnu packages netpbm) #:use-module (gnu packages perl) #:use-module (gnu packages pkg-config) #:use-module (gnu packages statistics) #:use-module (gnu packages web) #:use-module (gnu packages xml) #:use-module (srfi srfi-1)) ;;; Annotations (define-public r-org-eck12-eg-db (package (name "r-org-eck12-eg-db") (version "3.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "org.EcK12.eg.db" version 'annotation)) (sha256 (base32 "0c4p6jr83k0gm6pvn760yr8xf33wggrfcr6fg7a42a96bcf817gs")))) (properties `((upstream-name . 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Between 49 and 77 cells were captured at each of four time points (0, 24, 48, 72 hours) following serum switch using the Fluidigm C1 microfluidic system. RNA from each cell was isolated and used to construct mRNA-Seq libraries, which were then sequenced to a depth of ~4 million reads per library, resulting in a complete gene expression profile for each cell.") (license license:artistic2.0))) (define-public r-all (package (name "r-all") (version "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ALL" version 'experiment)) (sha256 (base32 "1z7kpjw4ndj6fkxwvhqf3gawhrn26ksrlns7j2c78qzxqmjndik9")))) (properties `((upstream-name . "ALL"))) (build-system r-build-system) (propagated-inputs (list r-biobase)) (home-page "https://bioconductor.org/packages/ALL") (synopsis "Acute Lymphoblastic Leukemia data from the Ritz laboratory") (description "The data consist of microarrays from 128 different individuals with @dfn{acute lymphoblastic leukemia} (ALL). 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It's possible, for example, to choose a specific @dfn{group of functionally associated genes} (GFAG) and observe the gene expression behavior with the plots created with the @code{GFAGtargetUi} function. Features such as differential expression and fold change can be easily seen with aid of the plots made with the @code{GFAGpathUi} function.") (license license:gpl2+))) (define-public r-adimpute (package (name "r-adimpute") (version "1.4.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ADImpute" version)) (sha256 (base32 "1bkq1hd8sqg9r28r70a9vd3gb2nsmg6dybf002d621p88cdfjib2")))) (properties `((upstream-name . 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The @code{ADImpute} package proposes two methods to address this issue: @enumerate @item a gene regulatory network-based approach using gene-gene relationships learnt from external data; @item a baseline approach corresponding to a sample-wide average. @end enumerate @code{ADImpute} implements these novel methods and also combines them with existing imputation methods like @code{DrImpute} and @code{SAVER}. @code{ADImpute} can learn the best performing method per gene and combine the results from different methods into an ensemble.") (license license:gpl3+))) (define-public r-adsplit (package (name "r-adsplit") (version "1.64.0") (source (origin (method url-fetch) (uri (bioconductor-uri "adSplit" version)) (sha256 (base32 "1b4ck371h3a76m5h0brvlzsyg1g6q5fjrhra5hqv9pwxr330h9r2")))) (properties `((upstream-name . 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(license license:gpl2+))) (define-public r-aggregatebiovar (package (name "r-aggregatebiovar") (version "1.4.0") (source (origin (method url-fetch) (uri (bioconductor-uri "aggregateBioVar" version)) (sha256 (base32 "1wbfp1pf62di6pzxsf36lmzk6y9dllz1n4iv3mhpb1x8cvy4hqqk")))) (properties `((upstream-name . "aggregateBioVar"))) (build-system r-build-system) (propagated-inputs (list r-matrix r-rlang r-s4vectors r-singlecellexperiment r-summarizedexperiment r-tibble)) (native-inputs (list r-knitr)) (home-page "https://github.com/jasonratcliff/aggregateBioVar") (synopsis "Differential gene expression analysis for multi-subject scRNA-seq") (description "This package @code{aggregateBioVar} contains tools to summarize single cell gene expression profiles at the level of subject for single cell RNA-seq data collected from more than one subject (e.g. biological sample or technical replicates). A @code{SingleCellExperiment} object is taken as input and converted to a list of @code{SummarizedExperiment} objects, where each list element corresponds to an assigned cell type. The @code{SummarizedExperiment} objects contain aggregate gene-by-subject count matrices and inter-subject column metadata for individual subjects that can be processed using downstream bulk RNA-seq tools.") (license license:gpl3))) (define-public r-agilp (package (name "r-agilp") (version "3.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "agilp" version)) (sha256 (base32 "02cyc2y4v3y16zlrnax2c96b2qfxj6b2j37ps4g2gdqgas08n9xp")))) (properties `((upstream-name . 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(license license:artistic2.0))) (define-public r-agimicrorna (package (name "r-agimicrorna") (version "2.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "AgiMicroRna" version)) (sha256 (base32 "0jic89gyphbv7jzlfgm9bh1aq48lp86rq6hr34gsg9z0pa1192xa")))) (properties `((upstream-name . "AgiMicroRna"))) (build-system r-build-system) (propagated-inputs (list r-affy r-affycoretools r-biobase r-limma r-preprocesscore)) (home-page "https://git.bioconductor.org/packages/AgiMicroRna") (synopsis "Processing and differential expression analysis of Agilent microRNA chips") (description "@code{AgiMicroRna} provides useful functionality for the processing, quality assessment and differential expression analysis of Agilent microRNA array data. The package uses a limma-like structure to generate the processed data in order to make statistical inferences about differential expression using the linear model features implemented in limma. Standard Bioconductor objects are used so that other packages could be used as well.") (license license:gpl3))) (define-public r-aneufinder (package (name "r-aneufinder") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "AneuFinder" version)) (sha256 (base32 "0xn8952fkchhx7m8dam6gjy86j551xp1cs67510s1qrmfgzpkjp0")))) (build-system r-build-system) (native-inputs (list r-knitr)) (propagated-inputs (list r-genomicranges r-aneufinderdata r-ecp r-foreach r-doparallel r-biocgenerics r-s4vectors r-genomeinfodb r-iranges r-rsamtools r-bamsignals r-dnacopy r-biostrings r-genomicalignments r-ggplot2 r-reshape2 r-ggdendro r-ggrepel r-reordercluster r-mclust r-cowplot)) (home-page "https://bioconductor.org/packages/AneuFinder/") (synopsis "Copy number variation analysis in single-cell-sequencing data") (description "This package implements functions for copy number variant calling, plotting, export and analysis from whole-genome single cell sequencing data.") 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(license license:artistic2.0))) (define-public r-vsn (package (name "r-vsn") (version "3.62.0") (source (origin (method url-fetch) (uri (bioconductor-uri "vsn" version)) (sha256 (base32 "03p2wdjbjnrn1ddyz0fbn04mdxpsmv83qhh3apj6azshl0bs1j2x")))) (build-system r-build-system) (propagated-inputs (list r-affy r-biobase r-ggplot2 r-lattice r-limma)) (native-inputs (list r-knitr)) ; for vignettes (home-page "https://bioconductor.org/packages/release/bioc/html/vsn.html") (synopsis "Variance stabilization and calibration for microarray data") (description "The package implements a method for normalising microarray intensities, and works for single- and multiple-color arrays. It can also be used for data from other technologies, as long as they have similar format. The method uses a robust variant of the maximum-likelihood estimator for an additive-multiplicative error model and affine calibration. The model incorporates data calibration step (a.k.a. normalization), a model for the dependence of the variance on the mean intensity and a variance stabilizing data transformation. Differences between transformed intensities are analogous to \"normalized log-ratios\". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.") (license license:artistic2.0))) ;; There is no source tarball, so we fetch the code from the Bioconductor git ;; repository. 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The result is a single output depicting the variation across all conditions. @code{XINA} not only extracts coabundance profiles within and across experiments, but also incorporates protein-protein interaction databases and integrative resources such as @dfn{Kyoto encyclopedia of genes and genomes} (KEGG) to infer interactors and molecular functions, respectively, and produces intuitive graphical outputs.") (license license:gpl3))) (define-public r-xmapbridge (package (name "r-xmapbridge") (version "1.52.0") (source (origin (method url-fetch) (uri (bioconductor-uri "xmapbridge" version)) (sha256 (base32 "1zsqhisbq6f9qgw9f0a6ixxh635h3qm17117yfns5nnfw73ndlgi")))) (properties `((upstream-name . "xmapbridge"))) (build-system r-build-system) (home-page "https://git.bioconductor.org/packages/xmapbridge") (synopsis "Display numeric data in the web based genome browser X:MAP") (description "The package @code{xmapbridge} can plot graphs in the X:Map genome browser. 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The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.") ;; Any version of the LGPL. (license license:lgpl3+))) (define r-rcppnumerical (package (name "r-rcppnumerical") (version "0.4-0") (source (origin (method url-fetch) (uri (cran-uri "RcppNumerical" version)) (sha256 (base32 "1a92fql6mijhnr1kxkcxwivf95pk9lhgmhzkshs51h0ybfv5krik")))) (properties `((upstream-name . "RcppNumerical"))) (build-system r-build-system) (propagated-inputs `(("r-rcpp" ,r-rcpp) ("r-rcppeigen" ,r-rcppeigen))) (native-inputs `(("r-knitr" ,r-knitr))) (home-page "https://github.com/yixuan/RcppNumerical") (synopsis "Rcpp integration for numerical computing libraries") (description "This package provides a collection of open source libraries for numerical computing (numerical integration, optimization, etc.) and their integration with @code{Rcpp}.") 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(license license:artistic2.0))) (define-public r-diffbind (package (name "r-diffbind") (version "3.4.11") (source (origin (method url-fetch) (uri (bioconductor-uri "DiffBind" version)) (sha256 (base32 "1xprj3x3s3yh6fwsdcl4zgfbhn640422x1lhhrmvdr836jr8sxcj")))) (properties `((upstream-name . "DiffBind"))) (build-system r-build-system) (propagated-inputs (list r-amap r-apeglm r-ashr r-biocparallel r-deseq2 r-dplyr r-genomicalignments r-genomicranges r-ggplot2 r-ggrepel r-gplots r-greylistchip r-iranges r-lattice r-limma r-locfit r-rcolorbrewer r-rcpp r-rhtslib r-rsamtools r-s4vectors r-summarizedexperiment r-systempiper)) (home-page "https://bioconductor.org/packages/DiffBind") (synopsis "Differential binding analysis of ChIP-Seq peak data") (description "This package computes differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions.") 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While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation.") 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Tests based on a variety of T- and F-statistics (including T-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with T-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted P-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.") 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Starting 2.0.5, new functions have been added for finding the peaks with bi-directional promoters with summary statistics (peaksNearBDP), for summarizing the occurrence of motifs in peaks (summarizePatternInPeaks) and for adding other IDs to annotated peaks or enrichedGO (addGeneIDs).") (license license:gpl2+))) (define-public r-matrixgenerics (package (name "r-matrixgenerics") (version "1.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MatrixGenerics" version)) (sha256 (base32 "1s75p8rrmj24r0vcbaiyw8xg8y84j388mv6iawai7pypfcl8s1z3")))) (properties `((upstream-name . "MatrixGenerics"))) (build-system r-build-system) (propagated-inputs (list r-matrixstats)) (home-page "https://bioconductor.org/packages/MatrixGenerics") (synopsis "S4 generic summary statistic functions for matrix-like objects") (description "This package provides S4 generic functions modeled after the @code{matrixStats} API for alternative matrix implementations. 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An \"intelligent\" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.") 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GOfuncR provides the standard candidate vs background enrichment analysis using the hypergeometric test, as well as three additional tests: @enumerate @item the Wilcoxon rank-sum test that is used when genes are ranked, @item a binomial test that is used when genes are associated with two counts, and @item a Chi-square or Fisher's exact test that is used in cases when genes are associated with four counts. @end enumerate To correct for multiple testing and interdependency of the tests, family-wise error rates are computed based on random permutations of the gene-associated variables. GOfuncR also provides tools for exploring the ontology graph and the annotations, and options to take gene-length or spatial clustering of genes into account. It is also possible to provide custom gene coordinates, annotations and ontologies.") 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In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.") (license license:gpl3))) (define-public r-ebimage (package (name "r-ebimage") (version "4.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "EBImage" version)) (sha256 (base32 "030vpn55ppfqq4408c4db4w40d17x1yq6zajb11p2glikvm1q619")))) (properties `((upstream-name . "EBImage"))) (build-system r-build-system) (propagated-inputs (list r-abind r-biocgenerics r-fftwtools r-htmltools r-htmlwidgets r-jpeg r-locfit r-png r-rcurl r-tiff)) (native-inputs (list r-knitr)) ; for vignettes (home-page "https://github.com/aoles/EBImage") (synopsis "Image processing and analysis toolbox for R") (description "EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. 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(license license:expat))) (define-public r-somaticsignatures (package (name "r-somaticsignatures") (version "2.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "SomaticSignatures" version)) (sha256 (base32 "1dxzfkvljnydv7kfybfa52dwcbkkci2r8gjspjf90k2bxf10phql")))) (properties `((upstream-name . "SomaticSignatures"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biostrings r-genomeinfodb r-genomicranges r-ggbio r-ggplot2 r-iranges r-nmf r-pcamethods r-proxy r-reshape2 r-s4vectors r-variantannotation)) (native-inputs (list r-knitr)) (home-page "https://github.com/juliangehring/SomaticSignatures") (synopsis "Somatic signatures") (description "This package identifies mutational signatures of @dfn{single nucleotide variants} (SNVs). It provides a infrastructure related to the methodology described in Nik-Zainal (2012, Cell), with flexibility in the matrix decomposition algorithms.") 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In particular, functions to perform a signature analysis with known signatures and a signature analysis on @dfn{stratified mutational catalogue} (SMC) are provided.") (license license:gpl3))) (define-public r-gcrma (package (name "r-gcrma") (version "2.66.0") (source (origin (method url-fetch) (uri (bioconductor-uri "gcrma" version)) (sha256 (base32 "0h7dl4if6skbcqdjdzqyghyswhwpx7xvb54lffz4wdaxpabp3001")))) (build-system r-build-system) (propagated-inputs (list r-affy r-affyio r-biobase r-biocmanager r-biostrings r-xvector)) (home-page "https://bioconductor.org/packages/gcrma/") (synopsis "Background adjustment using sequence information") (description "Gcrma adjusts for background intensities in Affymetrix array data which include optical noise and @dfn{non-specific binding} (NSB). The main function @code{gcrma} converts background adjusted probe intensities to expression measures using the same normalization and summarization methods as a @dfn{Robust Multiarray Average} (RMA). 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The model also accounts for the difference in library sizes and optionally for batch effects and/or other covariates, avoiding the need for pre-normalize the data.") (license license:artistic2.0))) (define-public r-zfpkm (package (name "r-zfpkm") (version "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "zFPKM" version)) (sha256 (base32 "0fk05vrmyyrhmkwi06lsi553mlpqj3fgwhk1kygz83iqv5z2vfw9")))) (properties `((upstream-name . "zFPKM"))) (build-system r-build-system) (propagated-inputs (list r-checkmate r-dplyr r-ggplot2 r-summarizedexperiment r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://github.com/ronammar/zFPKM/") (synopsis "Functions to facilitate zFPKM transformations") (description "This is a package to perform the zFPKM transform on RNA-seq FPKM data. This algorithm is based on the publication by Hart et al., 2013 (Pubmed ID 24215113).") (license license:gpl3))) (define-public r-rbowtie2 (package (name "r-rbowtie2") (version "2.0.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Rbowtie2" version)) (sha256 (base32 "0xpvrx2ak9x913sym4l46ycwbnmpcdwb3bf3dfd2gsp0krv8vh1x")))) (properties `((upstream-name . "Rbowtie2"))) (build-system r-build-system) (propagated-inputs (list r-magrittr r-rsamtools)) (inputs (list samtools zlib)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/Rbowtie2/") (synopsis "R wrapper for Bowtie2 and AdapterRemoval") (description "This package provides an R wrapper of the popular @code{bowtie2} sequencing reads aligner and @code{AdapterRemoval}, a convenient tool for rapid adapter trimming, identification, and read merging.") 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(license license:asl2.0))) (define-public r-arrmnormalization (package (name "r-arrmnormalization") (version "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ARRmNormalization" version)) (sha256 (base32 "1ryqr3mpakjml0jhbk28k2z511sdl87wxdczxq1rwx98s0pc9mnh")))) (properties `((upstream-name . "ARRmNormalization"))) (build-system r-build-system) (propagated-inputs (list r-arrmdata)) (home-page "https://bioconductor.org/packages/ARRmNormalization/") (synopsis "Adaptive robust regression normalization for methylation data") (description "This is a package to perform the @dfn{Adaptive Robust Regression method} (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay.") 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In the iClusterPlus model, binary observations such as somatic mutation are modeled as Binomial processes; categorical observations such as copy number states are realizations of Multinomial random variables; counts are modeled as Poisson random processes; and continuous measures are modeled by Gaussian distributions.") (license license:gpl2+))) (define-public r-rbowtie (package (name "r-rbowtie") (version "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Rbowtie" version)) (sha256 (base32 "0ardmryx6ac7v6n900a1klrrldvbmh7bxvy8ldz8rwid19h29ikr")))) (properties `((upstream-name . "Rbowtie"))) (build-system r-build-system) (arguments `(#:phases ;; Disable unsupported `popcnt' instructions on ;; architectures other than x86_64 ,(if (string-prefix? 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(license license:artistic2.0))) (define-public r-rhisat2 (package (name "r-rhisat2") (version "1.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Rhisat2" version)) (sha256 (base32 "092rws9vjxgm2jpkbp6ign47zmillyyidnc7ylcbn4zr9j5lwv0y")))) (properties `((upstream-name . "Rhisat2"))) (build-system r-build-system) (arguments `(#:phases (modify-phases %standard-phases (add-after 'unpack 'make-reproducible (lambda _ (substitute* "src/Makefile" (("`hostname`") "guix") (("`date`") "0") ;; Avoid shelling out to "which". (("^CC =.*") (which "gcc")) (("^CPP =.*") (which "g++"))) #t))))) (propagated-inputs (list r-genomicfeatures r-genomicranges r-sgseq)) (native-inputs (list r-knitr)) (home-page "https://github.com/fmicompbio/Rhisat2") (synopsis "R Wrapper for HISAT2 sequence aligner") (description "This package provides an R interface to the HISAT2 spliced short-read aligner by Kim et al. (2015). The package contains wrapper functions to create a genome index and to perform the read alignment to the generated index.") (license license:gpl3))) (define-public r-quasr (package (name "r-quasr") (version "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "QuasR" version)) (sha256 (base32 "0d292xgaq8d3cdpa9anabda03lis46xc29iw9c5k5i3sj7dcr4g5")))) (properties `((upstream-name . "QuasR"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-biobase r-biocgenerics r-biocparallel r-biostrings r-bsgenome r-genomeinfodb r-genomicfeatures r-genomicfiles r-genomicranges r-iranges r-rbowtie r-rhtslib r-rsamtools r-rtracklayer r-s4vectors r-shortread)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/QuasR/") (synopsis "Quantify and annotate short reads in R") (description "This package provides a framework for the quantification and analysis of short genomic reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest.") (license license:gpl2))) (define-public r-rqc (package (name "r-rqc") (version "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Rqc" version)) (sha256 (base32 "0hcxkrfja0gmd8r2llijdvaw2xiiplk037305inimz0qna6w2071")))) (properties `((upstream-name . "Rqc"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biocparallel r-biocstyle r-biostrings r-biovizbase r-genomicalignments r-genomicfiles r-ggplot2 r-iranges r-knitr r-markdown r-plyr r-rcpp r-reshape2 r-rsamtools r-s4vectors r-shiny r-shortread)) (native-inputs (list r-knitr)) (home-page "https://github.com/labbcb/Rqc") (synopsis "Quality control tool for high-throughput sequencing data") (description "Rqc is an optimized tool designed for quality control and assessment of high-throughput sequencing data. It performs parallel processing of entire files and produces a report which contains a set of high-resolution graphics.") (license license:gpl2+))) (define-public r-birewire (package (name "r-birewire") (version "3.26.5") (source (origin (method url-fetch) (uri (bioconductor-uri "BiRewire" version)) (sha256 (base32 "041i5d08bsc5jqx3309fixjacizs4yi992cwazxghm8mrk3kicbr")))) (properties `((upstream-name . "BiRewire"))) (build-system r-build-system) (propagated-inputs (list r-igraph r-matrix r-rtsne r-slam)) (home-page "https://bioconductor.org/packages/release/bioc/html/BiRewire.html") (synopsis "Tools for randomization of bipartite graphs") (description "This package provides functions for bipartite network rewiring through N consecutive switching steps and for the computation of the minimal number of switching steps to be performed in order to maximise the dissimilarity with respect to the original network. It includes functions for the analysis of the introduced randomness across the switching steps and several other routines to analyse the resulting networks and their natural projections.") (license license:gpl3))) (define-public r-birta (package (name "r-birta") (version "1.31.0") (source (origin (method url-fetch) (uri (bioconductor-uri "birta" version)) (sha256 (base32 "00a1kcfmcgdbx6wpnhk45wm45bynhry5m93l9hm75j2rwyc4lnca")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-limma r-mass)) (home-page "https://bioconductor.org/packages/birta") (synopsis "Bayesian inference of regulation of transcriptional activity") (description "Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. @dfn{birta} (Bayesian Inference of Regulation of Transcriptional Activity) uses the regulatory networks of transcription factors and miRNAs together with mRNA and miRNA expression data to predict switches in regulatory activity between two conditions. A Bayesian network is used to model the regulatory structure and Markov-Chain-Monte-Carlo is applied to sample the activity states.") (license license:gpl2+))) (define-public r-multidataset (package (name "r-multidataset") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MultiDataSet" version)) (sha256 (base32 "17asldnxqvp3sijx7nbi2lbbgnq4iq8z72qlg9080sm5lga1yy1s")))) (properties `((upstream-name . "MultiDataSet"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-genomicranges r-ggplot2 r-ggrepel r-iranges r-limma r-qqman r-s4vectors r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/MultiDataSet/") (synopsis "Implementation of MultiDataSet and ResultSet") (description "This package provides an implementation of the BRGE's (Bioinformatic Research Group in Epidemiology from Center for Research in Environmental Epidemiology) MultiDataSet and ResultSet. MultiDataSet is designed for integrating multi omics data sets and ResultSet is a container for omics results. This package contains base classes for MEAL and rexposome packages.") (license license:expat))) (define-public r-ropls (package (name "r-ropls") (version "1.26.4") (source (origin (method url-fetch) (uri (bioconductor-uri "ropls" version)) (sha256 (base32 "19f3wd55860x959h5n7mrivyjdas5b3jmx74lf24xnx23g26f8rn")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-multidataset)) (native-inputs (list r-knitr)) ; for vignettes (home-page "https://dx.doi.org/10.1021/acs.jproteome.5b00354") (synopsis "Multivariate analysis and feature selection of omics data") (description "Latent variable modeling with @dfn{Principal Component Analysis} (PCA) and @dfn{Partial Least Squares} (PLS) are powerful methods for visualization, regression, classification, and feature selection of omics data where the number of variables exceeds the number of samples and with multicollinearity among variables. @dfn{Orthogonal Partial Least Squares} (OPLS) enables to separately model the variation correlated (predictive) to the factor of interest and the uncorrelated (orthogonal) variation. While performing similarly to PLS, OPLS facilitates interpretation. This package provides imlementations of PCA, PLS, and OPLS for multivariate analysis and feature selection of omics data. In addition to scores, loadings and weights plots, the package provides metrics and graphics to determine the optimal number of components (e.g. with the R2 and Q2 coefficients), check the validity of the model by permutation testing, detect outliers, and perform feature selection (e.g. with Variable Importance in Projection or regression coefficients).") (license license:cecill))) (define-public r-biosigner (package (name "r-biosigner") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "biosigner" version)) (sha256 (base32 "189018qahyw33dmg73wa7k4rp8nzrx6ai8f2dr6vhbpcdc1gnm0z")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-e1071 r-multidataset r-randomforest r-ropls)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/biosigner/") (synopsis "Signature discovery from omics data") (description "Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets.") (license license:cecill))) (define-public r-annotatr (package (name "r-annotatr") (version "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "annotatr" version)) (sha256 (base32 "1ha2wn56cdab4p3wdwv4xlqjsgl7sd8phbx71qbclrbdwpq2mi7i")))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-annotationhub r-dplyr r-genomeinfodb r-genomicfeatures r-genomicranges r-ggplot2 r-iranges r-readr r-regioner r-reshape2 r-rtracklayer r-s4vectors)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/annotatr/") (synopsis "Annotation of genomic regions to genomic annotations") (description "Given a set of genomic sites/regions (e.g. ChIP-seq peaks, CpGs, differentially methylated CpGs or regions, SNPs, etc.) it is often of interest to investigate the intersecting genomic annotations. Such annotations include those relating to gene models (promoters, 5'UTRs, exons, introns, and 3'UTRs), CpGs (CpG islands, CpG shores, CpG shelves), or regulatory sequences such as enhancers. The annotatr package provides an easy way to summarize and visualize the intersection of genomic sites/regions with genomic annotations.") (license license:gpl3))) (define-public r-rsubread (package (name "r-rsubread") (version "2.8.2") (source (origin (method url-fetch) (uri (bioconductor-uri "Rsubread" version)) (sha256 (base32 "078zcchw9xl6vs2wihzzji349vq0m1a039m86jdlvb7nc3i1imfk")))) (properties `((upstream-name . "Rsubread"))) (build-system r-build-system) (inputs (list zlib)) (propagated-inputs (list r-matrix)) (home-page "https://bioconductor.org/packages/Rsubread/") (synopsis "Subread sequence alignment and counting for R") (description "This package provides tools for alignment, quantification and analysis of second and third generation sequencing data. It includes functionality for read mapping, read counting, SNP calling, structural variant detection and gene fusion discovery. It can be applied to all major sequencing techologies and to both short and long sequence reads.") (license license:gpl3))) (define-public r-flowutils (package (name "r-flowutils") (version "1.58.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowUtils" version)) (sha256 (base32 "0rgybkzbn8c3kpbz0ddghp1np0gka0cgiqvkk5jbnhlgf4s07161")))) (properties `((upstream-name . "flowUtils"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-corpcor r-flowcore r-graph r-runit r-xml)) (home-page "https://github.com/jspidlen/flowUtils") (synopsis "Utilities for flow cytometry") (description "This package provides utilities for flow cytometry data.") (license license:artistic2.0))) (define-public r-consensusclusterplus (package (name "r-consensusclusterplus") (version "1.58.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ConsensusClusterPlus" version)) (sha256 (base32 "13z43qbk9z7mvy8v8k185m6n020i6ahb18pm4q88rs75qlklzdkr")))) (properties `((upstream-name . "ConsensusClusterPlus"))) (build-system r-build-system) (propagated-inputs (list r-all r-biobase r-cluster)) (home-page "https://bioconductor.org/packages/ConsensusClusterPlus") (synopsis "Clustering algorithm") (description "This package provides an implementation of an algorithm for determining cluster count and membership by stability evidence in unsupervised analysis.") (license license:gpl2))) ;; This is the latest commit and it solves a bug from the latest release. (define-public r-cycombine (let ((commit "f18504bc83ff5daee2b5eb4b28f09abdaaa66698") (revision "1")) (package (name "r-cycombine") (version (git-version "0.2.6" revision commit)) (source (origin (method git-fetch) (uri (git-reference (url "https://github.com/biosurf/cyCombine") (commit commit))) (file-name (git-file-name name version)) (sha256 (base32 "1fiwnik8iahg01732fik85xhz359x32f1xc59h443pdf7jancskm")))) (properties `((upstream-name . "cyCombine"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-cytolib r-dplyr r-flowcore r-ggplot2 r-knitr r-kohonen r-magrittr r-purrr r-rcolorbrewer r-readr r-readxl r-stringr r-sva r-tibble r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://github.com/biosurf/cyCombine") (synopsis "Integration of single-cell cytometry datasets") (description "This package provides a method for combining single-cell cytometry datasets, which increases the analytical flexibility and the statistical power of the analyses while minimizing technical noise.") (license license:expat)))) (define-public r-cytolib (package (name "r-cytolib") (version "2.6.2") (source (origin (method url-fetch) (uri (bioconductor-uri "cytolib" version)) (sha256 (base32 "0ycr4wmkfi0rvzwicblkfjgppk72gwwpim0rfiz1s44lycsf4py5")))) (properties `((upstream-name . "cytolib"))) (build-system r-build-system) (native-inputs (list r-knitr)) (propagated-inputs (list r-bh r-rcpp r-rcpparmadillo r-rcppparallel r-rhdf5lib r-rprotobuflib)) (home-page "https://bioconductor.org/packages/cytolib/") (synopsis "C++ infrastructure for working with gated cytometry") (description "This package provides the core data structure and API to represent and interact with gated cytometry data.") (license license:artistic2.0))) (define-public r-flowcore (package (name "r-flowcore") (version "2.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowCore" version)) (sha256 (base32 "0zbd2hrdbb6r0np6nd3ab8nlcf9l57vcwnnhbqkbas8y0c2i2mwp")))) (properties `((upstream-name . "flowCore"))) (build-system r-build-system) (propagated-inputs (list r-bh r-biobase r-biocgenerics r-cytolib r-matrixstats r-rcpp r-rcpparmadillo r-rprotobuflib r-s4vectors)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/flowCore") (synopsis "Basic structures for flow cytometry data") (description "This package provides S4 data structures and basic functions to deal with flow cytometry data.") (license license:artistic2.0))) (define-public r-flowmeans (package (name "r-flowmeans") (version "1.54.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowMeans" version)) (sha256 (base32 "0iy8hvi0inj1ylhdx6q4mya9k55iazprz6fdrnq1mxb2iyndzsl6")))) (properties `((upstream-name . "flowMeans"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-feature r-flowcore r-rrcov)) (home-page "https://bioconductor.org/packages/flowMeans") (synopsis "Non-parametric flow cytometry data gating") (description "This package provides tools to identify cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection.") (license license:artistic2.0))) (define-public r-ncdfflow (package (name "r-ncdfflow") (version "2.40.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ncdfFlow" version)) (sha256 (base32 "1c6wb2x24ydqp5nxrx6bhj6f13x9djfy9awkc7zn63xkag7mvvar")))) (properties `((upstream-name . "ncdfFlow"))) (build-system r-build-system) (propagated-inputs (list r-bh r-biobase r-biocgenerics r-flowcore r-rcpp r-rcpparmadillo r-rhdf5lib r-zlibbioc)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/ncdfFlow/") (synopsis "HDF5 based storage for flow cytometry data") (description "This package provides HDF5 storage based methods and functions for manipulation of flow cytometry data.") (license license:artistic2.0))) (define-public r-ggcyto (package (name "r-ggcyto") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ggcyto" version)) (sha256 (base32 "17dnmsa92gc2za36c3klgd7rklqlxrhkzs5ksnrc1am6a4knc0p1")))) (properties `((upstream-name . "ggcyto"))) (build-system r-build-system) (propagated-inputs (list r-data-table r-flowcore r-flowworkspace r-ggplot2 r-gridextra r-hexbin r-ncdfflow r-plyr r-rcolorbrewer r-rlang r-scales)) (native-inputs (list r-knitr)) (home-page "https://github.com/RGLab/ggcyto/issues") (synopsis "Visualize Cytometry data with ggplot") (description "With the dedicated fortify method implemented for @code{flowSet}, @code{ncdfFlowSet} and @code{GatingSet} classes, both raw and gated flow cytometry data can be plotted directly with ggplot. The @code{ggcyto} wrapper and some custom layers also make it easy to add gates and population statistics to the plot.") (license license:artistic2.0))) (define-public r-flowviz (package (name "r-flowviz") (version "1.58.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowViz" version)) (sha256 (base32 "039sh7qn25gp2b34khs8dyrdpxyapsjlprrvxlz8f7dl8gmggl04")))) (properties `((upstream-name . "flowViz"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-flowcore r-hexbin r-idpmisc r-kernsmooth r-lattice r-latticeextra r-mass r-rcolorbrewer)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/flowViz/") (synopsis "Visualization for flow cytometry") (description "This package provides visualization tools for flow cytometry data.") (license license:artistic2.0))) (define-public r-flowclust (package (name "r-flowclust") (version "3.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowClust" version)) (sha256 (base32 "0ch7mkq40qcnxwgzy51vjdlwyzx4bvp03vpdm6dwjc6qy8a6qfzi")))) (properties `((upstream-name . "flowClust"))) (build-system r-build-system) (arguments `(#:configure-flags (list "--configure-args=--enable-bundled-gsl=no"))) (propagated-inputs (list r-biobase r-biocgenerics r-clue r-corpcor r-ellipse r-flowcore r-flowviz r-graph r-mnormt)) (inputs (list gsl)) (native-inputs (list pkg-config r-knitr)) (home-page "https://bioconductor.org/packages/flowClust") (synopsis "Clustering for flow cytometry") (description "This package provides robust model-based clustering using a t-mixture model with Box-Cox transformation.") (license license:artistic2.0))) ;; TODO: this package bundles an old version of protobuf. It's not easy to ;; make it use our protobuf package instead. (define-public r-rprotobuflib (package (name "r-rprotobuflib") (version "2.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "RProtoBufLib" version)) (sha256 (base32 "04qlhbhdchpr35rdc6jc3y8fy6znnfrdlsb8am04agbrvpjgrx10")))) (properties `((upstream-name . "RProtoBufLib"))) (build-system r-build-system) (arguments `(#:phases (modify-phases %standard-phases (add-after 'unpack 'unpack-bundled-sources (lambda _ (with-directory-excursion "src" (invoke "tar" "xf" "protobuf-3.13.0.tar.gz"))))))) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/RProtoBufLib/") (synopsis "C++ headers and static libraries of Protocol buffers") (description "This package provides the headers and static library of Protocol buffers for other R packages to compile and link against.") (license license:bsd-3))) (define-public r-flowworkspace (package (name "r-flowworkspace") (version "4.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowWorkspace" version)) (sha256 (base32 "11ni7kgk9s1fz3lvg85s6r7x2fhk4m7cdpilji05ya12jsyr3fig")))) (properties `((upstream-name . "flowWorkspace"))) (build-system r-build-system) (propagated-inputs (list r-aws-s3 r-aws-signature r-bh r-biobase r-biocgenerics r-cytolib r-data-table r-delayedarray r-digest r-dplyr r-flowcore r-ggplot2 r-graph r-lattice r-latticeextra r-matrixstats r-ncdfflow r-rbgl r-rcpp r-rcpparmadillo r-rcppparallel r-rgraphviz r-rhdf5lib r-rprotobuflib r-s4vectors r-scales r-xml)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/flowWorkspace/") (synopsis "Infrastructure for working with cytometry data") (description "This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the @code{flowCore} functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.") (license license:artistic2.0))) (define-public r-flowstats (package (name "r-flowstats") (version "4.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowStats" version)) (sha256 (base32 "0jjfq66m4lbpkynwxaparkd05znhp3jl9ccj37gyghly294x3rm9")))) (properties `((upstream-name . "flowStats"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-cluster r-fda r-flowcore r-flowviz r-flowworkspace r-kernsmooth r-ks r-lattice r-mass r-ncdfflow r-rcolorbrewer r-rrcov)) (home-page "http://www.github.com/RGLab/flowStats") (synopsis "Statistical methods for the analysis of flow cytometry data") (description "This package provides methods and functionality to analyze flow data that is beyond the basic infrastructure provided by the @code{flowCore} package.") (license license:artistic2.0))) (define-public r-opencyto (package (name "r-opencyto") (version "2.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "openCyto" version)) (sha256 (base32 "11svr1lk383pkm4npwrnf3h37b3drjsmcwcgdbb45x8k2k95z2fm")))) (properties `((upstream-name . "openCyto"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-clue r-data-table r-flowclust r-flowcore r-flowstats r-flowviz r-flowworkspace r-graph r-gtools r-ks r-lattice r-mass r-ncdfflow r-plyr r-r-utils r-rbgl r-rcolorbrewer r-rcpp r-rrcov)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/openCyto") (synopsis "Hierarchical gating pipeline for flow cytometry data") (description "This package is designed to facilitate the automated gating methods in a sequential way to mimic the manual gating strategy.") (license license:artistic2.0))) (define-public r-cytoml (package (name "r-cytoml") (version "2.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "CytoML" version)) (sha256 (base32 "16rgsc2dz5b8lm3ma8nh9wiknrdnvfjcsij7809rmcfs0gn1arcz")))) (properties `((upstream-name . "CytoML"))) (build-system r-build-system) (inputs (list libxml2 zlib)) (propagated-inputs (list r-base64enc r-bh r-biobase r-corpcor r-cytolib r-data-table r-dplyr r-flowcore r-flowworkspace r-ggcyto r-graph r-jsonlite r-lattice r-opencyto r-plyr r-rbgl r-rcpp r-rcpparmadillo r-rcppparallel r-rgraphviz r-rhdf5lib r-rprotobuflib r-runit r-tibble r-xml r-xml2 r-yaml)) (native-inputs (list r-knitr)) (home-page "https://github.com/RGLab/CytoML") (synopsis "GatingML interface for cross platform cytometry data sharing") (description "This package provides an interface to implementations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms.") (license license:artistic2.0))) (define-public r-flowsom (package (name "r-flowsom") (version "2.2.0") (source (origin (method url-fetch) (uri (bioconductor-uri "FlowSOM" version)) (sha256 (base32 "062xrv8li2z849qa8mv5dhafqli6ziz099ikjfvi7v2fr7174p8f")))) (properties `((upstream-name . "FlowSOM"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-colorramps r-consensusclusterplus r-cytoml r-dplyr r-flowcore r-flowworkspace r-ggforce r-ggnewscale r-ggplot2 r-ggpointdensity r-ggpubr r-ggrepel r-igraph r-magrittr r-pheatmap r-rcolorbrewer r-rlang r-rtsne r-scattermore r-tidyr r-xml)) (home-page "https://bioconductor.org/packages/FlowSOM/") (synopsis "Visualize and interpret cytometry data") (description "FlowSOM offers visualization options for cytometry data, by using self-organizing map clustering and minimal spanning trees.") (license license:gpl2+))) (define-public r-mixomics (package (name "r-mixomics") (version "6.18.1") (source (origin (method url-fetch) (uri (bioconductor-uri "mixOmics" version)) (sha256 (base32 "1wpskrnl2bry9m4k2djhjddcd8gpwf51gp5c3si1y7qxja78ql9f")))) (properties `((upstream-name . "mixOmics"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-corpcor r-dplyr r-ellipse r-ggrepel r-ggplot2 r-gridextra r-igraph r-lattice r-mass r-matrixstats r-rarpack r-rcolorbrewer r-reshape2 r-tidyr)) (native-inputs (list r-knitr)) (home-page "http://www.mixOmics.org") (synopsis "Multivariate methods for exploration of biological datasets") (description "mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data.") (license license:gpl2+))) (define-public r-depecher (package ;Source/Weave error (name "r-depecher") (version "1.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DepecheR" version)) (sha256 (base32 "1500jivij7zdycdd0i0b7mgp44w4z0hqnpzqbq8nhvzzdigic8x9")))) (properties `((upstream-name . "DepecheR"))) (build-system r-build-system) (propagated-inputs (list r-beanplot r-dosnow r-dplyr r-fnn r-foreach r-ggplot2 r-gmodels r-gplots r-mass r-matrixstats r-mixomics r-moments r-rcpp r-rcppeigen r-reshape2 r-robustbase r-viridis)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DepecheR/") (synopsis "Identify traits of clusters in high-dimensional entities") (description "The purpose of this package is to identify traits in a dataset that can separate groups. This is done on two levels. First, clustering is performed, using an implementation of sparse K-means. Secondly, the generated clusters are used to predict outcomes of groups of individuals based on their distribution of observations in the different clusters. As certain clusters with separating information will be identified, and these clusters are defined by a sparse number of variables, this method can reduce the complexity of data, to only emphasize the data that actually matters.") (license license:expat))) (define-public r-rcistarget (package (name "r-rcistarget") (version "1.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "RcisTarget" version)) (sha256 (base32 "1qarr7xd71kz1haccj65x7sc7pc4v6xpqcfa3rkyp2bk240gigi7")))) (properties `((upstream-name . "RcisTarget"))) (build-system r-build-system) (propagated-inputs (list r-arrow r-aucell r-biocgenerics r-data-table r-dplyr r-feather r-genomeinfodb r-genomicranges r-gseabase r-r-utils r-summarizedexperiment r-tibble)) (native-inputs (list r-knitr)) (home-page "https://aertslab.org/#scenic") (synopsis "Identify transcription factor binding motifs enriched on a gene list") (description "RcisTarget identifies @dfn{transcription factor binding motifs} (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the @dfn{transcription start site} (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high @dfn{Normalized Enrichment Score} (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).") (license license:gpl3))) (define-public r-chicago (package (name "r-chicago") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Chicago" version)) (sha256 (base32 "0nz9v37p7zl8yw3ykdbsb3izcwgx349wvrhwfyyn9h3jxjfafngn")))) (properties `((upstream-name . "Chicago"))) (build-system r-build-system) (propagated-inputs (list r-data-table r-delaporte r-hmisc r-mass r-matrixstats)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/Chicago") (synopsis "Capture Hi-C analysis of genomic organization") (description "This package provides a pipeline for analysing Capture Hi-C data.") (license license:artistic2.0))) (define-public r-cicero (package (name "r-cicero") (version "1.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "cicero" version)) (sha256 (base32 "1fc69nkm2cwpr6gkfmra2ph0lrmw486chswp4pn8i70ia43fzdm7")))) (build-system r-build-system) (propagated-inputs (list r-assertthat r-biobase r-biocgenerics r-data-table r-dplyr r-fnn r-genomicranges r-ggplot2 r-glasso r-gviz r-igraph r-iranges r-matrix r-monocle r-plyr r-reshape2 r-s4vectors r-stringi r-stringr r-tibble r-tidyr r-vgam)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/cicero/") (synopsis "Predict cis-co-accessibility from single-cell data") (description "Cicero computes putative cis-regulatory maps from single-cell chromatin accessibility data. It also extends the monocle package for use in chromatin accessibility data.") (license license:expat))) ;; This is the latest commit on the "monocle3" branch. (define-public r-cicero-monocle3 (let ((commit "fa2fb6515857a8cfc88bc9af044f34de1bcd2b7b") (revision "1")) (package (inherit r-cicero) (name "r-cicero-monocle3") (version (git-version "1.3.2" revision commit)) (source (origin (method git-fetch) (uri (git-reference (url "https://github.com/cole-trapnell-lab/cicero-release") (commit commit))) (file-name (git-file-name name version)) (sha256 (base32 "077yza93wdhi08n40md20jwk55k9lw1f3y0063qkk90cpz60wi0c")))) (propagated-inputs (modify-inputs (package-propagated-inputs r-cicero) (delete "r-monocle") (prepend r-monocle3)))))) (define-public r-circrnaprofiler (package (name "r-circrnaprofiler") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "circRNAprofiler" version)) (sha256 (base32 "0l83r9idhrha1m21vpnw917m5dlldji49zvx4d25m5g3ia1pkhpf")))) (properties `((upstream-name . "circRNAprofiler"))) (build-system r-build-system) (propagated-inputs (list r-annotationhub r-biostrings r-bsgenome r-bsgenome-hsapiens-ucsc-hg19 r-deseq2 r-dplyr r-edger r-genomeinfodb r-genomicranges r-ggplot2 r-gwascat r-iranges r-magrittr r-r-utils r-readr r-reshape2 r-rlang r-rtracklayer r-s4vectors r-seqinr r-stringi r-stringr r-universalmotif)) (native-inputs (list r-knitr)) (home-page "https://github.com/Aufiero/circRNAprofiler") (synopsis "Computational framework for the downstream analysis of circular RNA's") (description "@code{r-circrnaprofiler} is a computational framework for a comprehensive in silico analysis of @dfn{circular RNA} (circRNAs). This computational framework allows combining and analyzing circRNAs previously detected by multiple publicly available annotation-based circRNA detection tools. It covers different aspects of circRNAs analysis from differential expression analysis, evolutionary conservation, biogenesis to functional analysis.") (license license:gpl3))) (define-public r-cistopic (package (name "r-cistopic") (version "2.1.0") (source (origin (method git-fetch) (uri (git-reference (url "https://github.com/aertslab/cisTopic") (commit (string-append "v" version)))) (file-name (git-file-name name version)) (sha256 (base32 "0c4553rnxq7b1w451kcc3iwvak4qa5h2b43xmfw6ii8096zd1gbf")))) (build-system r-build-system) (propagated-inputs (list r-aucell r-data-table r-dplyr r-dosnow r-dt r-feather r-fitdistrplus r-genomicranges r-ggplot2 r-lda r-matrix r-plyr r-rcistarget r-rtracklayer r-s4vectors)) (home-page "https://github.com/aertslab/cisTopic") (synopsis "Modelling of cis-regulatory topics from single cell epigenomics data") (description "The sparse nature of single cell epigenomics data can be overruled using probabilistic modelling methods such as @dfn{Latent Dirichlet Allocation} (LDA). This package allows the probabilistic modelling of cis-regulatory topics (cisTopics) from single cell epigenomics data, and includes functionalities to identify cell states based on the contribution of cisTopics and explore the nature and regulatory proteins driving them.") (license license:gpl3))) (define-public r-cistopic-next (let ((commit "04cecbb9d1112fcc1a6edc28b5a506bcb49f2803") (revision "1")) (package (inherit r-cistopic) (name "r-cistopic-next") ;; The DESCRIPTION file says this is version 0.3.0, which is a bit odd ;; since the previous release is 2.1.0. Oh well. (version (git-version "0.3.0" revision commit)) (source (origin (method git-fetch) (uri (git-reference (url "https://github.com/aertslab/cisTopic") (commit commit))) (file-name (git-file-name name version)) (sha256 (base32 "11cg9szlysnsjiaahda4k5v2vh4rxx27zhz53hafgaq9mdz0kgi2")))) (properties `((upstream-name . "cisTopic"))) (propagated-inputs (list r-aucell r-data-table r-dosnow r-dplyr r-dt r-feather r-fitdistrplus r-genomicranges r-ggplot2 r-lda r-matrix r-plyr r-rcistarget r-rtracklayer r-s4vectors r-text2vec)) (native-inputs (list r-knitr))))) (define-public r-genie3 (package (name "r-genie3") (version "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "GENIE3" version)) (sha256 (base32 "0ms769267pimrx3xwwkgjy03qilkxxs7xwhzfca01f65i4n3l6fw")))) (properties `((upstream-name . "GENIE3"))) (build-system r-build-system) (propagated-inputs (list r-dplyr r-reshape2)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/GENIE3") (synopsis "Gene network inference with ensemble of trees") (description "This package implements the GENIE3 algorithm for inferring gene regulatory networks from expression data.") 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The method is based on comparing detected regions to a pooled null distribution, that can be implemented even when as few as two samples per population are available. Region-level statistics are obtained by fitting a @dfn{generalized least squares} (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.") (license license:expat))) (define-public r-omnipathr (package (name "r-omnipathr") (version "3.2.8") (source (origin (method url-fetch) (uri (bioconductor-uri "OmnipathR" version)) (sha256 (base32 "0vr16ar3rbjsfw4qz2g86lbhvmqwgq0vcahc6vrc4d9rdjxwg6sb")))) (properties `((upstream-name . 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(license license:expat))) (define-public r-biscuiteer (package (name "r-biscuiteer") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "biscuiteer" version)) (sha256 (base32 "16ds322b21g8ys5c3lkrvi70i82f9rxvnknbiqx4sp6f2l01j5yj")))) (properties `((upstream-name . 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(license license:gpl3+))) (define-public r-tricycle (package (name "r-tricycle") (version "1.2.1") (source (origin (method url-fetch) (uri (bioconductor-uri "tricycle" version)) (sha256 (base32 "19yh7yif8630j845m9rddva2z0xy4jcw9j4hvyr076jqbyxz998r")))) (properties `((upstream-name . "tricycle"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-circular r-dplyr r-genomicranges r-ggplot2 r-iranges r-rcolorbrewer r-s4vectors r-scater r-scattermore r-singlecellexperiment r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://github.com/hansenlab/tricycle") (synopsis "Transferable representation and inference of cell cycle") (description "The package contains functions to infer and visualize cell cycle process using Single-cell RNA-Seq data. It exploits the idea of transfer learning, projecting new data to the previous learned biologically interpretable space. 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(license license:gpl2))) (define-public r-phyloseq (package (name "r-phyloseq") (version "1.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "phyloseq" version)) (sha256 (base32 "0k0aj8f7g1vr7l0qcc507b3w67zc1k9x7sdblm7mjb20zqr3916s")))) (properties `((upstream-name . "phyloseq"))) (build-system r-build-system) (propagated-inputs (list r-ade4 r-ape r-biobase r-biocgenerics r-biomformat r-biostrings r-cluster r-data-table r-foreach r-ggplot2 r-igraph r-multtest r-plyr r-reshape2 r-scales r-vegan)) (native-inputs (list r-knitr)) (home-page "https://github.com/joey711/phyloseq") (synopsis "Handling and analysis of high-throughput microbiome census data") (description "Phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.") (license license:agpl3)))