;;; GNU Guix --- Functional package management for GNU ;;; Copyright © 2015-2024 Ricardo Wurmus ;;; Copyright © 2016, 2017, 2018, 2020, 2021 Roel Janssen ;;; Copyright © 2016 Pjotr Prins ;;; Copyright © 2016 Ben Woodcroft ;;; Copyright © 2017, 2022, 2024 Efraim Flashner ;;; Copyright © 2017, 2018, 2019, 2020, 2021 Tobias Geerinckx-Rice ;;; Copyright © 2019, 2020, 2021, 2022, 2023 Simon Tournier ;;; Copyright © 2020 Peter Lo ;;; Copyright © 2020-2023 Mădălin Ionel Patrașcu ;;; Copyright © 2020 Jakub Kądziołka ;;; Copyright © 2021 Hong Li ;;; Copyright © 2021 Tim Howes ;;; Copyright © 2021 Nicolas Vallet ;;; Copyright © 2023 Navid Afkhami ;;; ;;; 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 gexp) #:use-module (guix utils) #:use-module (guix git-download) #:use-module (guix build-system r) #:use-module (gnu packages) #:use-module (gnu packages algebra) #:use-module (gnu packages autotools) #:use-module (gnu packages base) #:use-module (gnu packages bioinformatics) #:use-module (gnu packages boost) #:use-module (gnu packages chemistry) #: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 java) #:use-module (gnu packages javascript) #:use-module (gnu packages maths) #:use-module (gnu packages ncurses) #:use-module (gnu packages netpbm) #:use-module (gnu packages python) #:use-module (gnu packages perl) #:use-module (gnu packages pkg-config) #:use-module (gnu packages protobuf) #:use-module (gnu packages statistics) #:use-module (gnu packages tls) #:use-module (gnu packages web) #:use-module (gnu packages xml) #:use-module ((srfi srfi-1) #:hide (zip))) ;;; Annotations (define-public r-bsgenome-hsapiens-ucsc-hg38-masked (package (name "r-bsgenome-hsapiens-ucsc-hg38-masked") (version "1.4.5") (source (origin (method url-fetch) (uri (bioconductor-uri "BSgenome.Hsapiens.UCSC.hg38.masked" version 'annotation)) (sha256 (base32 "0j71hdxqvvc0s8mc6jp6zk502mrf095qazj95yzzb4rm6sjvd20m")))) (properties `((upstream-name . 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(license license:expat)))) (define-public r-methylclockdata (package (name "r-methylclockdata") (version "1.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "methylclockData" version 'experiment)) (sha256 (base32 "1bwrgib7k71i4i6iq4l71n0z9adq3bg9k8j10bpi79ygn9169np5")))) (properties `((upstream-name . "methylclockData"))) (build-system r-build-system) (propagated-inputs (list r-experimenthub r-experimenthubdata)) (native-inputs (list r-knitr)) (home-page "https://github.com/isglobal-brge/methylclockData") (synopsis "Data for methylclock package") (description "This package contains a collection of 9 datasets, andrews and bakulski cord blood, blood gse35069, blood gse35069 chen, blood gse35069 complete, combined cord blood, cord bloo d gse68456, gervin and lyle cord blood, guintivano dlpfc and saliva gse48472. The data are used to estimate cell counts using Extrinsic epigenetic age acceleration (EEAA) method. It also contains a collection of 12 datasets to use with @code{MethylClock} package to estimate chronological and gestational DNA methylation with estimators to use with different methylation clocks.") (license license:expat))) (define-public r-mousegastrulationdata (package (name "r-mousegastrulationdata") (version "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MouseGastrulationData" version 'experiment)) (sha256 (base32 "0adw98vym1jir1jrzaws7zrlfvls6rfl8bvkpq5sjy4crb33lxy2")))) (properties `((upstream-name . 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It includes a subset from 500-850 m/z and 1190-1310 seconds, including MS2 and MS3, intensity threshold 100.000; extracts from FTICR Apex III, m/z 400-450; a subset of UPLC - Bruker micrOTOFq data, both mzML and mz5; LC-MSMS and MRM files from proteomics experiments; and PSI mzIdentML example files for various search engines.") (license license:gpl2+))) (define-public r-msexperiment (package (name "r-msexperiment") (version "1.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MsExperiment" version)) (sha256 (base32 "0dxv3jw5aj1i73vqrp3c031pj26i7rp0q2zs4nq3x1vni349506d")))) (properties `((upstream-name . 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These data are then hosted on the @code{ExperimentHub}. Data used in this package was obtained from the @code{MSigDB} of the Broad Institute. Metadata for each gene set is stored along with the gene set in the @code{GeneSet} class object.") (license license:cc-by4.0))) (define-public r-pasilla (package (name "r-pasilla") (version "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "pasilla" version 'experiment)) (sha256 (base32 "0r5i64125qq5z4c8zliazsi68035d1bsz6ingzqdh37m8prdw1cr")))) (build-system r-build-system) (propagated-inputs (list r-dexseq)) (native-inputs (list r-knitr)) (home-page "https://www.bioconductor.org/packages/pasilla/") (synopsis "Data package with per-exon and per-gene read counts") (description "This package provides per-exon and per-gene read counts computed for selected genes from RNA-seq data that were presented in the article 'Conservation of an RNA regulatory map between Drosophila and mammals' by Brooks et al., Genome Research 2011.") 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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 "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ALL" version 'experiment)) (sha256 (base32 "1yl8b8q8i19kx4viwinhyq9xn9d4axlfgjvm7cpf7pys4krhnrha")))) (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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This package also includes commonly used gene set data based on KEGG pathways and GO terms for major research species, including human, mouse, rat and budding yeast. Mapping data between common gene IDs for budding yeast are also included.") (license license:gpl2+))) (define-public r-curatedtcgadata (package (name "r-curatedtcgadata") (version "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "curatedTCGAData" version 'experiment)) (sha256 (base32 "1xdygjwqgy6kjjxzvsy25bckc0f8j5m42wrj1vrnwy5fp0q7y287")))) (properties `((upstream-name . 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This software infers differential expression directly by the counts difference between conditions. It assumes that the sum counts difference between conditions follow a negative binomial distribution. In addition, @code{ABSSeq} moderates the fold-changes by two steps: the expression level and gene-specific dispersion, that might facilitate the gene ranking by fold-change and visualization.") (license license:gpl3+))) (define-public r-adacgh2 (package (name "r-adacgh2") (version "2.44.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ADaCGH2" version)) (sha256 (base32 "1j9dn0xw8mdfvi2ccm1d5j9q740wb89wqi6715n6jy3dljlc8irz")))) (properties `((upstream-name . 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(license license:gpl3+))) (define-public r-adam (package (name "r-adam") (version "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ADAM" version)) (sha256 (base32 "0z0rmpwfhd8p6c4zscviwsningsm740r3pb95cl8brasfdg1kl3v")))) (properties `((upstream-name . "ADAM"))) (build-system r-build-system) (propagated-inputs (list r-dplyr r-dt r-go-db r-keggrest r-knitr r-pbapply r-rcpp r-stringr r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/ADAM") (synopsis "Gene activity and diversity analysis module") (description "This software @code{ADAM} is a @dfn{Gene set enrichment analysis} (GSEA) package created to group a set of genes from comparative samples (control versus experiment) belonging to different species according to their respective functions. 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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 "1.74.0") (source (origin (method url-fetch) (uri (bioconductor-uri "adSplit" version)) (sha256 (base32 "13rrkb0vxkknvqhb8pgx8d13sxzy3w0wbkhhj5lrlc1kb1yqcfbh")))) (properties `((upstream-name . 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(add-after 'install 'strip-jar-timestamps (assoc-ref ant:%standard-phases 'strip-jar-timestamps))))) (inputs (list (list openjdk11 "jdk") java-pj)) (propagated-inputs (list r-apcluster r-biobase r-biocparallel r-corpcor r-dmwr2 r-geometry r-nmf r-nnls r-pcapp r-rjava r-summarizedexperiment)) (native-inputs (list r-knitr zip)) ;zip is needed for repacking the jar (home-page "https://bioconductor.org/packages/debCAM") (synopsis "Deconvolution by convex analysis of mixtures") (description "This package is an R implementation for fully unsupervised deconvolution of complex tissues. DebCAM provides basic functions to perform unsupervised deconvolution on mixture expression profiles by @acronym{CAM, Convex Analysis of Mixtures} and some auxiliary functions to help understand the subpopulation- specific results. It also implements functions to perform supervised deconvolution based on prior knowledge of molecular markers, S matrix or A matrix. Combining molecular markers from CAM and from prior knowledge can achieve semi-supervised deconvolution of mixtures.") (license license:gpl2))) (define-public r-decipher (package (name "r-decipher") (version "3.0.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DECIPHER" version)) (sha256 (base32 "1bgzl3sy4l5xfgxrkw8z1dvygkn2dgcl2fl9ah13ggs8hc9h9nlm")))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-dbi r-iranges r-s4vectors r-xvector)) (home-page "https://www.bioconductor.org/packages/DECIPHER/") (synopsis "Tools for deciphering and managing biological sequences") (description "This package provides a toolset for deciphering and managing biological sequences.") (license license:gpl3))) (define-public r-deco (package (name "r-deco") (version "1.13.0") (source (origin (method url-fetch) (uri (bioconductor-uri "deco" version)) (sha256 (base32 "0d4abif3v62cbas6hl7pfw8q8jihh7nsra76k9cm6kz54qw4fbnw")))) (properties `((upstream-name . 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(license license:gpl3+))) (define-public r-decomplexdisease (package (name "r-decomplexdisease") (version "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DEComplexDisease" version)) (sha256 (base32 "12gw9b0gdwyih51j2gzay6vxhycgc52n8svd0slv6wsbw5rc19lh")))) (properties `((upstream-name . "DEComplexDisease"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-complexheatmap r-deseq2 r-edger r-rcpp r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DEComplexDisease") (synopsis "Investigations of complex diseases by bi-clustering analysis") (description "DEComplexDisease is designed to find the @acronym{DEGs, Differential Expressed Genes} for complex disease, which is characterized by the heterogeneous genomic expression profiles. Different from the established DEG analysis tools, it does not assume the patients of complex diseases to share the common DEGs. By applying a bi-clustering algorithm, DEComplexDisease finds the DEGs shared by as many patients. Applying the DEComplexDisease analysis results, users are possible to find the patients affected by the same mechanism based on the shared signatures.") (license license:gpl3))) (define-public r-decomptumor2sig (package (name "r-decomptumor2sig") (version "2.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "decompTumor2Sig" version)) (sha256 (base32 "1pnxnxz9zsxqs7cbxgkjapr57k2m1d57w5hak0dwcy5zcxjzmai8")))) (properties `((upstream-name . 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(license license:gpl2))) (define-public r-deconrnaseq (package (name "r-deconrnaseq") (version "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DeconRNASeq" version)) (sha256 (base32 "0hwvfsc48dakh3nvz60i92yciz2m5my9w57kzpyj4jyk92cs181g")))) (properties `((upstream-name . "DeconRNASeq"))) (build-system r-build-system) (propagated-inputs (list r-ggplot2 r-limsolve r-pcamethods)) (home-page "https://bioconductor.org/packages/DeconRNASeq") (synopsis "Deconvolution of heterogeneous tissue samples for mRNA-Seq data") (description "DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It models the expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.") (license license:gpl2))) (define-public r-decontam (package (name "r-decontam") (version "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "decontam" version)) (sha256 (base32 "1xjd9jzxlj6gfd6fnygzm21q1wy5x5pl031sq1q0svq3jlnzvgb7")))) (properties `((upstream-name . "decontam"))) (build-system r-build-system) (propagated-inputs (list r-ggplot2 r-reshape2)) (native-inputs (list r-knitr)) (home-page "https://github.com/benjjneb/decontam") (synopsis "Identification of contaminants in marker-gene and metagenomics data") (description "This package offers simple statistical identification of contaminating sequence features in marker-gene or metagenomics data. It works on any kind of feature derived from environmental sequencing data (e.g. ASVs, OTUs, taxonomic groups, MAGs, etc). Requires DNA quantitation data or sequenced negative control samples.") (license license:artistic2.0))) (define-public r-deconvr (package (name "r-deconvr") (version "1.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "deconvR" version)) (sha256 (base32 "181dxjj8bzy1b9xq9hd3m3ak1698w7j0sf8h9g0bhf3blzlj4pmi")))) (properties `((upstream-name . "deconvR"))) (build-system r-build-system) (propagated-inputs (list r-assertthat r-biocgenerics r-data-table r-dplyr r-e1071 r-foreach r-genomicranges r-iranges r-magrittr r-mass r-matrixstats r-methylkit r-minfi r-nnls r-quadprog r-rsq r-s4vectors r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://github.com/BIMSBbioinfo/deconvR") (synopsis "Simulation and deconvolution of omic profiles") (description "This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types. The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally, we included @code{BSmeth2Probe}, to make mapping WGBS data to their probe IDs easier.") (license license:artistic2.0))) (define-public r-decoupler (package (name "r-decoupler") (version "2.9.7") (source (origin (method url-fetch) (uri (bioconductor-uri "decoupleR" version)) (sha256 (base32 "0zi6shh1dn8kli66dyywwgy1s809yms0jrl6lkwvzn88rms7yaqb")))) (properties `((upstream-name . 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It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.") (license license:gpl3))) (define-public r-deepsnv (package (name "r-deepsnv") (version "1.50.0") (source (origin (method url-fetch) (uri (bioconductor-uri "deepSNV" version)) (sha256 (base32 "1rcq2bg4z6z7czqi662w5gsdc1vd4p8vb353hqayhciv31dz51fr")))) (properties `((upstream-name . 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(license license:gpl3))) (define-public r-degreport (package (name "r-degreport") (version "1.40.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DEGreport" version)) (sha256 (base32 "087c7x3vz8z3yz4jdwbcskdqmv3kgz4c4vi3r9gvvay5z36yhpl5")) (snippet '(delete-file "docs/jquery.sticky-kit.min.js")))) (properties `((upstream-name . 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It integrates some of the code mentioned in DESeq2 and @code{edgeR} vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.") (license license:expat))) (define-public r-delayedarray (package (name "r-delayedarray") (version "0.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DelayedArray" version)) (sha256 (base32 "1hjkh8xsqlfwhwxs3snpx9in58plv67aj9gsw1x8842kxfric7m7")))) (properties `((upstream-name . "DelayedArray"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-iranges r-matrix r-matrixgenerics r-s4arrays r-s4vectors r-sparsearray)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DelayedArray") (synopsis "Delayed operations on array-like objects") (description "Wrapping an array-like object (typically an on-disk object) in a @code{DelayedArray} object allows one to perform common array operations on it without loading the object in memory. 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This can help to create visualisations that are more representative of heterogeneity in the original high-dimensional space.") (license license:expat))) (define-public r-derfinder (package (name "r-derfinder") (version "1.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "derfinder" version)) (sha256 (base32 "1i4m20wb08zncksz415jl8bd5r4gdygk7324cp6xhijrc1pfzl1i")))) (properties `((upstream-name . 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(license license:artistic2.0))) (define-public r-derfinderhelper (package (name "r-derfinderhelper") (version "1.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "derfinderHelper" version)) (sha256 (base32 "0186wjrszf6c5amibmdblabx3cfvq7p7k6kza38gahw0p7ibwv21")))) (properties `((upstream-name . "derfinderHelper"))) (build-system r-build-system) (propagated-inputs (list r-iranges r-matrix r-s4vectors)) (native-inputs (list r-knitr)) (home-page "https://github.com/leekgroup/derfinderHelper") (synopsis "Helper for derfinder") (description "This package speeds up the derfinder package when using multiple cores. It is particularly useful when using BiocParallel and it helps reduce the time spent loading the full derfinder package when running the F-statistics calculation in parallel.") (license license:artistic2.0))) (define-public r-dmrcate (package (name "r-dmrcate") (version "3.0.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DMRcate" version)) (sha256 (base32 "1s83p6chchsx68qsfzqclpl3wq6fqy2r3namr8l3rrxp9b49342i")))) (properties `((upstream-name . "DMRcate"))) (build-system r-build-system) (propagated-inputs (list r-annotationhub r-biomart r-bsseq r-edger r-experimenthub r-genomeinfodb r-genomicranges r-gviz r-iranges r-limma r-minfi r-missmethyl r-plyr r-s4vectors r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DMRcate") (synopsis "Methylation array and sequencing spatial analysis methods") (description "This is a package for de novo identification and extraction of @dfn{differentially methylated regions} (DMRs) from the human genome using @dfn{Whole Genome Bisulfite Sequencing} (WGBS) and Illumina Infinium Array (450K and EPIC) data. It provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. It includes @code{GRanges} generation and plotting functions.") ;; GPLv3 with additional liability disclaimer. (license license:gpl3))) (define-public r-drimseq (package (name "r-drimseq") (version "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DRIMSeq" version)) (sha256 (base32 "10skx3n3r9vp1p1499ddccgabi7q3cy1dpi5pbp4ap0gff5ika5x")))) (properties `((upstream-name . "DRIMSeq"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biocparallel r-edger r-genomicranges r-ggplot2 r-iranges r-limma r-mass r-reshape2 r-s4vectors)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DRIMSeq") (synopsis "Differential transcript usage and tuQTL analyses with Dirichlet-multinomial model in RNA-seq") (description "The package provides two frameworks. One for the differential transcript usage analysis between different conditions and one for the tuQTL analysis. Both are based on modeling the counts of genomic features (i.e., transcripts) with the Dirichlet-multinomial distribution. The package also makes available functions for visualization and exploration of the data and results.") (license license:gpl3+))) (define-public r-dropletutils (package (name "r-dropletutils") (version "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DropletUtils" version)) (sha256 (base32 "01y88cnii02sn1jgyvvmbx8j60qbzqyznqfxzv06yi4y0xj37klg")))) (properties `((upstream-name . 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(define-public r-dsb (package (name "r-dsb") (version "1.0.3") (source (origin (method url-fetch) (uri (cran-uri "dsb" version)) (sha256 (base32 "1xzhd4q04c1vql49r6m4zskpx7f5hkl5hmdgr3gsbxb73xfs51v2")))) (properties `((upstream-name . "dsb"))) (build-system r-build-system) (propagated-inputs (list r-limma r-magrittr r-mclust)) (native-inputs (list r-knitr r-rmarkdown)) (home-page "https://github.com/niaid/dsb") (synopsis "Normalize & denoise droplet single cell protein data (CITE-Seq)") (description "R-dsb improves protein expression analysis in droplet-based single-cell studies. The package specifically addresses noise in raw protein UMI counts from methods like CITE-seq. It identifies and removes two main sources of noise—protein-specific noise from unbound antibodies and droplet/cell-specific noise. The package is applicable to various methods, including CITE-seq, REAP-seq, ASAP-seq, TEA-seq, and Mission Bioplatform data. Check the vignette for tutorials on integrating dsb with Seurat and Bioconductor, and using dsb in Python.") (license license:cc0))) (define-public r-dss (package (name "r-dss") (version "2.52.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DSS" version)) (sha256 (base32 "1y9xg6ic3a03xswyfvyxdhnd7ngkljc96bm5fry4ni6kpa77bkv8")))) (properties `((upstream-name . "DSS"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocparallel r-bsseq)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DSS") (synopsis "Dispersion shrinkage for sequencing data") (description "DSS is an R library performing differential analysis for count-based sequencing data. It detects @dfn{differentially expressed genes} (DEGs) from RNA-seq, and differentially methylated loci or regions (DML/DMRs) from @dfn{bisulfite sequencing} (BS-seq). The core of DSS is a dispersion shrinkage method for estimating the dispersion parameter from Gamma-Poisson or Beta-Binomial distributions.") ;; Any version of the GPL (license (list license:gpl2+ license:gpl3+)))) (define-public r-dyndoc (package (name "r-dyndoc") (version "1.82.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DynDoc" version)) (sha256 (base32 "174jfdyq7g7mvn7wvmdkf36n0n969aqsg9bwd1nk6a5nw1khm7js")))) (properties `((upstream-name . "DynDoc"))) (build-system r-build-system) (home-page "https://bioconductor.org/packages/DynDoc") (synopsis "Dynamic document tools") (description "This package provides a set of functions to create and interact with dynamic documents and vignettes.") 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(define-public r-absfiltergsea (package (name "r-absfiltergsea") (version "1.5.1") (source (origin (method url-fetch) (uri (cran-uri "AbsFilterGSEA" version)) (sha256 (base32 "15srxkxsvn38kd5frdrwfdf0ad8gskrd0h01wmdf9hglq8fjrp7w")))) (properties `((upstream-name . "AbsFilterGSEA"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-deseq r-limma r-rcpp r-rcpparmadillo)) (home-page "https://cran.r-project.org/web/packages/AbsFilterGSEA/") (synopsis "Improved false positive control of gene-permuting with absolute filtering") (description "This package provides a function that performs gene-permuting of a gene-set enrichment analysis (GSEA) calculation with or without the absolute filtering. Without filtering, users can perform (original) two-tailed or one-tailed absolute GSEA.") (license license:gpl2))) ;; This is a CRAN package, but it depends on r-biobase from Bioconductor. (define-public r-bisquerna (package (name "r-bisquerna") (version "1.0.5") (source (origin (method url-fetch) (uri (cran-uri "BisqueRNA" version)) (sha256 (base32 "0p3p5lp69gri7vs6qfpm7br4ksbs4l7clm4nj8ki99wpqiqni23n")))) (properties `((upstream-name . "BisqueRNA"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-limsolve)) (native-inputs (list r-knitr)) (home-page "https://www.biorxiv.org/content/10.1101/669911v1") (synopsis "Decomposition of bulk expression with single-cell sequencing") (description "This package provides tools to accurately estimate cell type abundances from heterogeneous bulk expression. A reference-based method utilizes single-cell information to generate a signature matrix and transformation of bulk expression for accurate regression based estimates. A marker-based method utilizes known cell-specific marker genes to measure relative abundances across samples.") (license license:gpl3))) ;; This is a CRAN package, but it depends on r-bsgenome-hsapiens-ucsc-hg19 ;; from Bioconductor. (define-public r-deconstructsigs (package (name "r-deconstructsigs") (version "1.8.0") (source (origin (method url-fetch) (uri (cran-uri "deconstructSigs" version)) (sha256 (base32 "014x0nb23jb98666kaav2phkvmkr38pi38jv0dqd4jv7zp0gdf1a")))) (properties `((upstream-name . "deconstructSigs"))) (build-system r-build-system) (propagated-inputs (list r-bsgenome r-bsgenome-hsapiens-ucsc-hg19 r-genomeinfodb r-reshape2)) (home-page "https://github.com/raerose01/deconstructSigs") (synopsis "Identifies signatures present in a tumor sample") (description "This package takes sample information in the form of the fraction of mutations in each of 96 trinucleotide contexts and identifies the weighted combination of published signatures that, when summed, most closely reconstructs the mutational profile.") 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(define-public r-netgsa (package (name "r-netgsa") (version "4.0.5") (source (origin (method url-fetch) (uri (cran-uri "netgsa" version)) (sha256 (base32 "1m9myxsbvbljr038azxzakpbh20a21qhiy20d0ipvjc5asq3kfla")))) (properties `((upstream-name . "netgsa"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-corpcor r-data-table r-dplyr r-genefilter r-glassofast r-glmnet r-graph r-graphite r-httr r-igraph r-magrittr r-matrix r-msigdbr r-org-hs-eg-db r-quadprog r-rcpp r-rcppeigen r-rcy3 r-reshape2 r-rlang)) (native-inputs (list r-knitr)) (home-page "https://github.com/mikehellstern/netgsa") (synopsis "Network-Based gene set analysis") (description "This package lets you carry out network-based gene set analysis by incorporating external information about interactions among genes, as well as novel interactions learned from data. 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(snippet '(for-each delete-file '("inst/doc/MMUPHin.R" "inst/doc/MMUPHin.html"))))) (properties `((upstream-name . "MMUPHin"))) (build-system r-build-system) (arguments (list #:phases #~(modify-phases %standard-phases (add-after 'unpack 'fix-includes (lambda _ (substitute* "inst/doc/MMUPHin.Rmd" (("\\.\\./man/figures") (string-append (getcwd) "/man/figures")) (("bibliography: references.bib") (string-append "bibliography: " (getcwd) "/vignettes/references.bib"))))) ;; Maaslin2 generates log files with timestamps. We don't need to ;; keep them. The generated PDF files also contain timestamps, so ;; we replace them with arbitrary fixed timestamps. (add-after 'check 'make-reproducible (lambda _ (for-each delete-file (find-files #$output "maaslin2.log")) (with-fluids ((%default-port-encoding "ISO-8859-1")) (substitute* (find-files #$output "\\.pdf$") (("/CreationDate \\(D:.*\\)") "/CreationDate (D:20230301143558)") (("/ModDate \\(D:.*\\)") "/ModDate (D:20230301143558)")))))))) ;; The DESCRIPTION file says that glpk is needed, but this package does ;; not seem to reference the library directly. (propagated-inputs (list r-cowplot r-dplyr r-fpc r-ggplot2 r-igraph r-maaslin2 r-metafor r-stringr r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/MMUPHin") (synopsis "Meta-analysis with uniform pipeline for heterogeneity in microbiome") (description "MMUPHin is an R package for meta-analysis tasks of microbiome cohorts. It has function interfaces for: @itemize @item covariate-controlled batch- and cohort effect adjustment; @item meta-analysis differential abundance testing; @item meta-analysis unsupervised discrete structure (clustering) discovery; @item meta-analysis unsupervised continuous structure discovery. @end itemize") (license license:expat))) (define-public r-modstrings (package (name "r-modstrings") (version "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Modstrings" version)) (sha256 (base32 "0yc8gsgxlww2g9z1m6jl02aqmama10fkr2mvibvdi01s5pqwdbky")))) (properties `((upstream-name . "Modstrings"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biostrings r-crayon r-genomicranges r-iranges r-s4vectors r-stringi r-stringr r-xvector)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/Modstrings") (synopsis "Working with modified nucleotide sequences") (description "Representing nucleotide modifications in a nucleotide sequence is usually done via special characters from a number of sources. This represents a challenge to work with in R and the Biostrings package. The Modstrings package implements this functionallity for RNA and DNA sequences containing modified nucleotides by translating the character internally in order to work with the infrastructure of the Biostrings package. For this the @code{ModRNAString} and @code{ModDNAString} classes and derivates and functions to construct and modify these objects despite the encoding issues are implemenented. In addition the conversion from sequences to list like location information (and the reverse operation) is implemented as well.") (license license:artistic2.0))) (define-public r-motifrg (package (name "r-motifrg") (version "1.31.0") (source (origin (method url-fetch) (uri (bioconductor-uri "motifRG" version)) (sha256 (base32 "1ml6zyzlk8yjbnfhga2qnw8nl43rankvka0kc1yljxr2b66aqbhn")))) (properties `((upstream-name . "motifRG"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-bsgenome r-bsgenome-hsapiens-ucsc-hg19 r-iranges r-seqlogo r-xvector)) (home-page "https://bioconductor.org/packages/motifRG") (synopsis "Discover motifs in high throughput sequencing data") (description "This package provides tools for discriminative motif discovery in high throughput genetic sequencing data sets using regression methods.") (license license:artistic2.0))) (define-public r-muscat (package (name "r-muscat") (version "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "muscat" version)) (sha256 (base32 "1gafcq3p693f28gz3p8hk8mlxd9zja95h8953sr56n7krfffy1gi")))) (properties `((upstream-name . "muscat"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-blme r-complexheatmap r-data-table r-deseq2 r-dplyr r-edger r-ggplot2 r-glmmtmb r-limma r-lme4 r-lmertest r-matrix r-matrixstats r-progress r-purrr r-s4vectors r-scales r-scater r-sctransform r-scuttle r-singlecellexperiment r-summarizedexperiment r-variancepartition r-viridis)) (native-inputs (list r-knitr)) (home-page "https://github.com/HelenaLC/muscat") (synopsis "Multi-sample multi-group scRNA-seq data analysis tools") (description "This package @code{muscat} provides various methods and visualization tools for @dfn{DS}(differential splicing) analysis in multi-sample, multi-group, multi-(cell-)subpopulation scRNA-seq data, including cell-level mixed models and methods based on aggregated \"pseudobulk\" data, as well as a flexible simulation platform that mimics both single and multi-sample scRNA-seq data.") (license license:gpl3))) (define-public r-mutationalpatterns (package (name "r-mutationalpatterns") (version "3.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MutationalPatterns" version)) (sha256 (base32 "0smf4l023ckwsm5ckrqqw7kjyi1awp378mzhab7v8nk9n5smsj61")))) (build-system r-build-system) (native-inputs (list r-knitr)) (propagated-inputs (list r-biocgenerics r-biostrings r-bsgenome ;; These two packages are suggested packages r-bsgenome-hsapiens-1000genomes-hs37d5 r-bsgenome-hsapiens-ucsc-hg19 r-cowplot r-dplyr r-genomeinfodb r-genomicranges r-ggalluvial r-ggdendro r-ggplot2 r-iranges r-magrittr r-nmf r-pracma r-purrr r-rcolorbrewer r-s4vectors r-stringr r-tibble r-tidyr r-variantannotation)) (home-page "https://bioconductor.org/packages/MutationalPatterns/") (synopsis "Extract and visualize mutational patterns in genomic data") (description "This package provides an extensive toolset for the characterization and visualization of a wide range of mutational patterns in SNV base substitution data.") (license license:expat))) (define-public r-msa (package (name "r-msa") (version "1.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "msa" version)) (sha256 (base32 "05i6pp10nn4icl51rx3b48s861hnd1yx72d933fphm6a5082zxms")))) (properties `((upstream-name . "msa"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biostrings r-iranges r-rcpp r-s4vectors)) (native-inputs (list r-knitr)) (home-page "http://www.bioinf.jku.at/software/msa/") (synopsis "Multiple sequence alignment") (description "The msa package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.") (license license:gpl2+))) (define-public r-msnbase (package (name "r-msnbase") (version "2.30.1") (source (origin (method url-fetch) (uri (bioconductor-uri "MSnbase" version)) (sha256 (base32 "0cdvi2mjvhj0h8x2rh3kkzrdnmzhr7d9a41m21r6b843a0q7hp6f")))) (properties `((upstream-name . "MSnbase"))) (build-system r-build-system) (propagated-inputs (list r-affy r-biobase r-biocgenerics r-biocparallel r-digest r-ggplot2 r-impute r-iranges r-lattice r-maldiquant r-mass r-mscoreutils r-mzid r-mzr r-pcamethods r-plyr r-protgenerics r-psmatch r-rcpp r-s4vectors r-scales r-vsn)) (native-inputs (list r-knitr)) (home-page "https://github.com/lgatto/MSnbase") (synopsis "Base functions and classes for MS-based proteomics") (description "This package provides basic plotting, data manipulation and processing of mass spectrometry based proteomics data.") (license license:artistic2.0))) (define-public r-msnid (package (name "r-msnid") (version "1.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MSnID" version)) (sha256 (base32 "0misrm4x4z5h8dfwcrwi24nhcjslqvbyk5n7qz6kf2zcgcwq8q44")))) (properties `((upstream-name . "MSnID"))) (build-system r-build-system) (arguments `(#:phases (modify-phases %standard-phases (add-after 'unpack 'set-HOME (lambda _ (setenv "HOME" "/tmp")))))) (propagated-inputs (list r-annotationdbi r-annotationhub r-biobase r-biocgenerics r-biocstyle r-biostrings r-data-table r-doparallel r-dplyr r-foreach r-ggplot2 r-iterators r-msmstests r-msnbase r-mzid r-mzr r-protgenerics r-purrr r-r-cache r-rcpp r-reshape2 r-rlang r-runit r-stringr r-tibble r-xtable)) (home-page "https://bioconductor.org/packages/MSnID") (synopsis "Utilities for LC-MSn proteomics identifications") (description "This package extracts @dfn{tandem mass spectrometry} (MS/MS) ID data from mzIdentML (leveraging the mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. It also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.") (license license:artistic2.0))) (define-public r-mzid (package (name "r-mzid") (version "1.42.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mzID" version)) (sha256 (base32 "0kh9swzh3hvi6qi64cgr13f22s1mgvz2rid5psb1gy4l3biwadj5")))) (properties `((upstream-name . "mzID"))) (build-system r-build-system) (propagated-inputs (list r-doparallel r-foreach r-iterators r-plyr r-protgenerics r-xml)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/mzID") (synopsis "Parser for mzIdentML files") (description "This package provides a parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less pretty output than a vendor specific parser.") (license license:gpl2+))) (define-public r-mzr (package (name "r-mzr") (version "2.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mzR" version)) (sha256 (base32 "02dz23xns9ryz98nip1w68h9q5ckxpyl1zvzklsp4j7p9z2400dk")) (modules '((guix build utils))) (snippet '(delete-file-recursively "src/boost")))) (properties `((upstream-name . "mzR") (updater-extra-inputs . ("boost")))) (build-system r-build-system) (arguments `(#:phases (modify-phases %standard-phases (add-after 'unpack 'use-system-boost (lambda _ (substitute* "src/Makevars" (("\\./boost/libs.*") "") (("PKG_LIBS=") "PKG_LIBS=$(BOOST_LIBS) ") (("\\ARCH_OBJS=" line) (string-append line "\nBOOST_LIBS=-lboost_system -lboost_regex \ -lboost_iostreams -lboost_thread -lboost_filesystem -lboost_chrono\n")))))))) (inputs (list boost ; use this instead of the bundled boost sources zlib)) (propagated-inputs (list r-biobase r-biocgenerics r-ncdf4 r-protgenerics r-rcpp r-rhdf5lib)) (native-inputs (list r-knitr)) (home-page "https://github.com/sneumann/mzR/") (synopsis "Parser for mass spectrometry data files") (description "The mzR package provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a wrapper for the ISB random access parser for mass spectrometry mzXML, mzData and mzML files. The package contains the original code written by the ISB, and a subset of the proteowizard library for mzML and mzIdentML. The netCDF reading code has previously been used in XCMS.") (license license:artistic2.0))) ;; This is a CRAN package, but it depends on a Bioconductor package. (define-public r-numbat (package (name "r-numbat") (version "1.3.2-1") (source (origin (method url-fetch) (uri (cran-uri "numbat" version)) (sha256 (base32 "1b9bykgw3z7a8bky5yv2g402gdapv8kcla2kbbyqvs77x4wba4q4")))) (properties `((upstream-name . "numbat"))) (build-system r-build-system) (propagated-inputs (list r-ape r-catools r-data-table r-dendextend r-dplyr r-genomicranges r-ggplot2 r-ggraph r-ggtree r-glue r-igraph r-iranges r-logger r-magrittr r-matrix r-optparse r-paralleldist r-patchwork r-pryr r-purrr r-r-utils r-rcpp r-rcpparmadillo r-rhpcblasctl r-roptim r-scales r-scistreer r-stringr r-tibble r-tidygraph r-tidyr r-vcfr r-zoo)) (home-page "https://github.com/kharchenkolab/numbat") (synopsis "Haplotype-aware CNV analysis from scRNA-Seq") (description "This package provides a computational method that infers copy number variations (CNV) in cancer scRNA-seq data and reconstructs the tumor phylogeny. It integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. It does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). It can be used to: @enumerate @item detect allele-specific copy number variations from single-cells @item differentiate tumor versus normal cells in the tumor microenvironment @item infer the clonal architecture and evolutionary history of profiled tumors @end enumerate For details on the method see @url{https://doi.org/10.1038/s41587-022-01468-y, Gao et al in Nature Biotechnology 2022}.") (license license:expat))) (define-public r-organism-dplyr (package (name "r-organism-dplyr") (version "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Organism.dplyr" version)) (sha256 (base32 "03z5pyqbaxwyrq5m858c8k69fwvclq98ksr84dc4m7r8lzz2hfxx")))) (properties `((upstream-name . "Organism.dplyr"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-annotationfilter r-biocfilecache r-dbi r-dbplyr r-dplyr r-genomeinfodb r-genomicfeatures r-genomicranges r-iranges r-rlang r-rsqlite r-s4vectors r-tibble)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/Organism.dplyr") (synopsis "Dplyr-based access to Bioconductor annotation resources") (description "This package provides an alternative interface to Bioconductor @code{ annotation} resources, in particular the gene identifier mapping functionality of the @code{org} packages (e.g., @code{org.Hs.eg.db}) and the genome coordinate functionality of the @code{TxDb} packages (e.g., @code{TxDb.Hsapiens.UCSC.hg38.knownGene}).") (license license:artistic2.0))) (define-public r-organismdbi (package (name "r-organismdbi") (version "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "OrganismDbi" version)) (sha256 (base32 "1cfh632rpmklmyd5cibwiy0i2pk2kk2m39g8mq5sxfwd2am4r0jk")))) (properties `((upstream-name . "OrganismDbi"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-biobase r-biocgenerics r-biocmanager r-dbi r-genomicfeatures r-genomicranges r-graph r-iranges r-rbgl r-s4vectors r-txdbmaker)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/OrganismDbi") (synopsis "Software to enable the smooth interfacing of database packages") (description "The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.") (license license:artistic2.0))) (define-public r-oscope (package (name "r-oscope") (version "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Oscope" version)) (sha256 (base32 "16d2ngakdg73rdx0bf1pz3z1n8npjzl3b7dn94g9zbayw4vp3x5z")))) (properties `((upstream-name . "Oscope"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-cluster r-ebseq r-testthat)) (home-page "https://bioconductor.org/packages/Oscope") (synopsis "Oscillatory genes identifier in unsynchronized single cell RNA-seq") (description "Oscope is a oscillatory genes identifier in unsynchronized single cell RNA-seq. This statistical pipeline has been developed to identify and recover the base cycle profiles of oscillating genes in an unsynchronized single cell RNA-seq experiment. The Oscope pipeline includes three modules: a sine model module to search for candidate oscillator pairs; a K-medoids clustering module to cluster candidate oscillators into groups; and an extended nearest insertion module to recover the base cycle order for each oscillator group.") (license license:asl2.0))) (define-public r-pcaexplorer (package (name "r-pcaexplorer") (version "2.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "pcaExplorer" version)) (sha256 (base32 "1szl2gyhw55ad4phcb7qn14amjb6xg65l3p4hnjzp6rda2cy9437")))) (properties `((upstream-name . "pcaExplorer"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-base64enc r-biomart r-deseq2 r-dt r-genefilter r-genomicranges r-ggplot2 r-ggrepel r-go-db r-gostats r-heatmaply r-iranges r-knitr r-limma r-nmf r-pheatmap r-plotly r-plyr r-rmarkdown r-s4vectors r-scales r-shiny r-shinyace r-shinybs r-shinydashboard r-summarizedexperiment r-threejs r-tidyr r-topgo)) (native-inputs (list r-knitr)) (home-page "https://github.com/federicomarini/pcaExplorer") (synopsis "Interactive Visualization of RNA-seq Data Using a Principal Components Approach") (description "This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.") (license license:expat))) (define-public r-pcamethods (package (name "r-pcamethods") (version "1.96.0") (source (origin (method url-fetch) (uri (bioconductor-uri "pcaMethods" version)) (sha256 (base32 "1hrq0xmpr1l95hyi6ls9r86ahwf2rcbvr8m7cpg6ra0gsfyn4mpi")))) (properties `((upstream-name . "pcaMethods"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-mass r-rcpp)) (home-page "https://github.com/hredestig/pcamethods") (synopsis "Collection of PCA methods") (description "This package provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results.") (license license:gpl3+))) (define-public r-pfamanalyzer (package (name "r-pfamanalyzer") (version "1.4.0") (source (origin (method url-fetch) (uri (bioconductor-uri "pfamAnalyzeR" version)) (sha256 (base32 "06bp5nghgrj8qyzqp1v869vck1j10093r9dp67w0kav4x4srkyyl")))) (properties `((upstream-name . "pfamAnalyzeR"))) (build-system r-build-system) (propagated-inputs (list r-dplyr r-magrittr r-readr r-stringr r-tibble)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/pfamAnalyzeR") (synopsis "Identification of domain isotypes in pfam data") (description "This R package enables the user to read pfam predictions into R. Most human protein domains exist as multiple distinct variants termed domain isotypes. This R package enables the identification and classification of such domain isotypes from pfam data.") (license license:expat))) (define-public r-piano (package (name "r-piano") (version "2.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "piano" version)) (sha256 (base32 "0v168wkwxzh70h2c08ad4dzlgklbgvx1fzwrzw2mqq0fyczj0diw")))) (properties `((upstream-name . "piano"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-dt r-fgsea r-gplots r-htmlwidgets r-igraph r-marray r-relations r-scales r-shiny r-shinydashboard r-shinyjs r-visnetwork)) (native-inputs (list r-knitr)) (home-page "https://varemo.github.io/piano/") (synopsis "Platform for integrative analysis of omics data") (description "Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. The package contains functions for combining the results of multiple runs of gene set analyses.") (license license:gpl2+))) (define-public r-polyester (package (name "r-polyester") (version "1.39.0") (source (origin (method url-fetch) (uri (bioconductor-uri "polyester" version)) (sha256 (base32 "0fw0qhmbygjq4ryspyqikb8rxfn33ks000j7sshgfg8hf2rmqg3x")))) (properties `((upstream-name . "polyester"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-iranges r-limma r-logspline r-s4vectors r-zlibbioc)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/polyester") (synopsis "Simulate RNA-seq reads") (description "The polyester package simulates RNA-seq reads from differential expression experiments with replicates. The reads can then be aligned and used to perform comparisons of methods for differential expression.") (license license:artistic2.0))) (define-public r-powertcr (package (name "r-powertcr") (version "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "powerTCR" version)) (sha256 (base32 "04w6jhpc1vkqrm3dr5igp1iwkammmi53mqafjz694n379hamxrhg")))) (properties `((upstream-name . "powerTCR"))) (build-system r-build-system) (propagated-inputs (list r-cubature r-doparallel r-evmix r-foreach r-magrittr r-purrr r-truncdist r-vegan r-vgam)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/powerTCR") (synopsis "Model-based comparative analysis of the TCR repertoire") (description "This package provides a model for the clone size distribution of the @acronym{TCR, T-cell receptor} repertoire. Further, it permits comparative analysis of TCR repertoire libraries based on theoretical model fits.") (license license:artistic2.0))) ;; This is a CRAN package, but it depends on a Bioconductor package: ;; r-aroma-light, r-dnacopy.. (define-public r-pscbs (package (name "r-pscbs") (version "0.67.0") (source (origin (method url-fetch) (uri (cran-uri "PSCBS" version)) (sha256 (base32 "1gnd2nkh587dqpnbk5fsai7hx261vm405550rhlxffvs366x3596")))) (properties `((upstream-name . "PSCBS"))) (build-system r-build-system) (arguments `(#:phases (modify-phases %standard-phases (add-before 'install 'change-home-dir (lambda _ ;; Change from /homeless-shelter to /tmp for write permission. (setenv "HOME" "/tmp")))))) (propagated-inputs (list r-aroma-light r-dnacopy r-future r-listenv r-matrixstats r-r-cache r-r-methodss3 r-r-oo r-r-utils)) (native-inputs (list r-r-rsp ;used to build vignettes r-r-devices)) (home-page "https://github.com/HenrikBengtsson/PSCBS") (synopsis "Analysis of parent-specific DNA copy numbers") (description "This is a package for segmentation of allele-specific DNA copy number data and detection of regions with abnormal copy number within each parental chromosome. Both tumor-normal paired and tumor-only analyses are supported.") (license license:gpl2+))) (define-public r-psmatch (package (name "r-psmatch") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "PSMatch" version)) (sha256 (base32 "13w145is3d95392qqdq6qh3mrlcixbj0jzz4r590xas1qjp5d03h")))) (properties `((upstream-name . "PSMatch"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biocparallel r-igraph r-matrix r-mscoreutils r-protgenerics r-qfeatures r-s4vectors)) (native-inputs (list r-knitr)) (home-page "https://github.com/RforMassSpectrometry/PSM") (synopsis "Handling and managing peptide spectrum matches") (description "The PSMatch package helps proteomics practitioners to load, handle and manage peptide spectrum matches. It provides functions to model peptide-protein relations as adjacency matrices and connected components, visualise these as graphs and make informed decision about shared peptide filtering. The package also provides functions to calculate and visualise MS2 fragment ions.") (license license:artistic2.0))) (define-public r-protgear (package (name "r-protgear") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "protGear" version)) (sha256 (base32 "1wbdp7f55lbn0gcxgnp9xk0y5npn7jmk9vp7yq9v76j7f396vj2f")))) (properties `((upstream-name . "protGear"))) (build-system r-build-system) (arguments (list #:phases '(modify-phases %standard-phases ;; Needed by styler for writing to caches. 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(define-public r-scgate (package (name "r-scgate") (version "1.6.2") (source (origin (method url-fetch) (uri (cran-uri "scGate" version)) (sha256 (base32 "0zlbrvr6lxcihspfqgpvv5kyrzqqpy3451j0kpnqc0n93bbs4cqk")))) (properties `((upstream-name . 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The q-value of a test measures the proportion of false positives incurred when that particular test is called significant. The local FDR measures the posterior probability the null hypothesis is true given the test's p-value. Various plots are automatically generated, allowing one to make sensible significance cut-offs. 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 . 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(license license:gpl2))) (define-public r-mbecs (package (name "r-mbecs") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MBECS" version)) (sha256 (base32 "15nv5rbw158d071gscms6p42wzf6ibnabiqcq256rcz6j0r69b63")))) (properties `((upstream-name . "MBECS"))) (build-system r-build-system) (arguments (list #:phases #~(modify-phases %standard-phases (add-after 'unpack 'set-HOME ;; Fontconfig needs a writable cache (lambda _ (setenv "HOME" "/tmp")))))) (propagated-inputs (list r-cluster r-dplyr r-ggplot2 r-gridextra r-limma r-lme4 r-lmertest r-magrittr r-matrix r-pheatmap r-phyloseq r-rmarkdown r-ruv r-sva r-tibble r-tidyr r-vegan)) (native-inputs (list r-knitr)) (home-page "https://github.com/rmolbrich/MBECS") (synopsis "Evaluation and correction of batch effects in microbiome data-sets") (description "The @acronym{MBECS, Microbiome Batch Effect Correction Suite} provides a set of functions to evaluate and mitigate unwated noise due to processing in batches. 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(license license:artistic2.0))) (define-public r-mbkmeans (package (name "r-mbkmeans") (version "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mbkmeans" version)) (sha256 (base32 "0fnf6ymbcfchhlcbwpwlcq1jc3lfzh9f8mf76xfy7vrpwngds1fs")))) (build-system r-build-system) (native-inputs (list r-knitr)) (propagated-inputs (list r-beachmat r-benchmarkme r-biocparallel r-clusterr r-delayedarray r-matrix r-rcpp r-rcpparmadillo r-rhdf5lib r-s4vectors r-singlecellexperiment r-summarizedexperiment)) (home-page "https://bioconductor.org/packages/mbkmeans") (synopsis "Mini-batch k-means clustering for single-cell RNA-seq") (description "This package implements the mini-batch k-means algorithm for large datasets, including support for on-disk data representation.") (license license:expat))) (define-public r-multibac (package (name "r-multibac") (version "1.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MultiBaC" version)) (sha256 (base32 "0m08620sii9181y0vlcrw9nbcnp4vnjjxvp96iqlgg5fsb23wbl7")))) (properties `((upstream-name . "MultiBaC"))) (build-system r-build-system) (propagated-inputs (list r-ggplot2 r-matrix r-multiassayexperiment r-pcamethods r-plotrix r-ropls)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/MultiBaC") (synopsis "Multiomic batch effect correction") (description "MultiBaC is a strategy to correct batch effects from multiomic datasets distributed across different labs or data acquisition events. MultiBaC is able to remove batch effects across different omics generated within separate batches provided that at least one common omic data type is included in all the batches considered.") (license license:gpl3))) (define-public r-multtest (package (name "r-multtest") (version "2.60.0") (source (origin (method url-fetch) (uri (bioconductor-uri "multtest" version)) (sha256 (base32 "04dv5rcqwpv0im7j3hvcj8hjybgs4a384zgnjyqbcipcicd2rjz4")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-mass r-survival)) (home-page "https://bioconductor.org/packages/multtest") (synopsis "Resampling-based multiple hypothesis testing") (description "This package can do non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. 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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(define-public r-perfmeas (package (name "r-perfmeas") (version "1.2.5") (source (origin (method url-fetch) (uri (cran-uri "PerfMeas" version)) (sha256 (base32 "13yjk0kwpbsqwl056hzf0zj2br1mk4faqcn1whdfxmq348c14hjb")))) (properties `((upstream-name . "PerfMeas"))) (build-system r-build-system) (propagated-inputs (list r-graph r-limma r-rbgl)) (home-page "https://cran.r-project.org/web/packages/PerfMeas/") (synopsis "Performance measures for ranking and classification tasks") (description "This package implements different performance measures for classification and ranking tasks. @dfn{Area under curve} (AUC), precision at a given recall, F-score for single and multiple classes are available.") (license license:gpl2+))) (define-public r-pepsnmr (package (name "r-pepsnmr") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "PepsNMR" version)) (sha256 (base32 "0z3kw8j972zmrcyikag5js20zpgc3l5bgkn5q31dzi1q7ynpkwhv")))) (properties `((upstream-name . 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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 "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MatrixGenerics" version)) (sha256 (base32 "1r7n5p89460h47mnfh190184dbcmrbj0j5d7dswkfwh6ixan3zyc")))) (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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"mia"))) (build-system r-build-system) (propagated-inputs (list r-ape r-biocgenerics r-biocparallel r-biostrings r-bluster r-decipher r-decontam r-delayedarray r-delayedmatrixstats r-dirichletmultinomial r-dplyr r-iranges r-mass r-matrixgenerics r-multiassayexperiment r-rlang r-s4vectors r-scater r-scuttle r-singlecellexperiment r-summarizedexperiment r-tibble r-tidyr r-treesummarizedexperiment r-vegan)) (native-inputs (list r-knitr)) (home-page "https://github.com/microbiome/mia") (synopsis "Microbiome analysis") (description "The mia package implements tools for microbiome analysis based on the @code{SummarizedExperiment}, @code{SingleCellExperiment} and @code{TreeSummarizedExperiment} infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.") (license license:artistic2.0))) (define-public r-microbiome (package (name "r-microbiome") (version "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "microbiome" version)) (sha256 (base32 "1azxfydcrxi46j6lykspzchwcj0dpghjia7vfb2bppz9gh8nvk37")))) (properties `((upstream-name . "microbiome"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-compositions r-dplyr r-ggplot2 r-phyloseq r-reshape2 r-rtsne r-scales r-tibble r-tidyr r-vegan)) (native-inputs (list r-knitr)) (home-page "https://microbiome.github.io/microbiome/") (synopsis "Tools for microbiome analysis") (description "This package facilitates phyloseq exploration and analysis of taxonomic profiling data. This package provides tools for the manipulation, statistical analysis, and visualization of taxonomic profiling data. In addition to targeted case-control studies, microbiome facilitates scalable exploration of population cohorts. This package supports the independent phyloseq data format and expands the available toolkit in order to facilitate the standardization of the analyses and the development of best practices.") (license license:bsd-2))) ;; This is a CRAN package but it depends on phyloseq, which is from ;; Bioconductor. (define-public r-microbiomestat (package (name "r-microbiomestat") (version "1.2") (source (origin (method url-fetch) (uri (cran-uri "MicrobiomeStat" version)) (sha256 (base32 "1kpc68sl63k104xy7r6f3gxan0yx0rs7ksn8ldbq8xla00ddflgq")))) (properties `((upstream-name . 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"miloR"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biocneighbors r-biocparallel r-biocsingular r-cowplot r-dplyr r-edger r-ggbeeswarm r-ggplot2 r-ggraph r-ggrepel r-gtools r-igraph r-irlba r-limma r-matrix r-matrixgenerics r-matrixstats r-numderiv r-patchwork r-rcolorbrewer r-rcpp r-rcpparmadillo r-s4vectors r-singlecellexperiment r-stringr r-summarizedexperiment r-tibble r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://marionilab.github.io/miloR") (synopsis "Differential neighbourhood abundance testing on a graph") (description "Milo performs single-cell differential abundance testing. Cell states are modelled as representative neighbourhoods on a nearest neighbour graph. Hypothesis testing is performed using a negative bionomial generalized linear model.") (license license:gpl3))) (define-public r-minfi (package (name "r-minfi") (version "1.50.0") (source (origin (method url-fetch) (uri (bioconductor-uri "minfi" version)) (sha256 (base32 "1hk44wddcygh4j7jmj1b0p40hf5qdy1m78x14j19h7z9aq4azdij")))) (build-system r-build-system) (propagated-inputs (list r-beanplot r-biobase r-biocgenerics r-biocparallel r-biostrings r-bumphunter r-data-table r-delayedarray r-delayedmatrixstats r-genefilter r-genomeinfodb r-genomicranges r-geoquery r-hdf5array r-illuminaio r-iranges r-lattice r-limma r-mass r-mclust r-nlme r-nor1mix r-preprocesscore r-quadprog r-rcolorbrewer r-reshape r-s4vectors r-siggenes r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://github.com/hansenlab/minfi") (synopsis "Analyze Illumina Infinium DNA methylation arrays") (description "This package provides tools to analyze and visualize Illumina Infinium methylation arrays.") (license license:artistic2.0))) (define-public r-missmethyl (package (name "r-missmethyl") (version "1.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "missMethyl" version)) (sha256 (base32 "0fnqa7v6lgld4pdqnvgdzly73aj4a4cn8sgszicxsyn1damxsjiw")))) (properties `((upstream-name . 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The test for differential variability is based on an empirical Bayes version of Levene's test. Differential methylation testing is performed using RUV, which can adjust for systematic errors of unknown origin in high-dimensional data by using negative control probes. Gene ontology analysis is performed by taking into account the number of probes per gene on the array, as well as taking into account multi-gene associated probes.") (license license:gpl2))) (define-public r-methylumi (package (name "r-methylumi") (version "2.50.0") (source (origin (method url-fetch) (uri (bioconductor-uri "methylumi" version)) (sha256 (base32 "1ms3w43yvy810mr6dml9hqp3kw5jlpr9153kd62gvhjsgikaj3ja")))) (build-system r-build-system) (propagated-inputs (list r-annotate r-annotationdbi r-biobase r-biocgenerics r-fdb-infiniummethylation-hg19 r-genefilter r-genomeinfodb r-genomicfeatures r-genomicranges r-ggplot2 r-illuminaio r-iranges r-lattice r-matrixstats r-minfi r-reshape2 r-s4vectors r-scales r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/methylumi") (synopsis "Handle Illumina methylation data") (description "This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. 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.") (license license:gpl2))) (define-public r-lefser (package (name "r-lefser") (version "1.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "lefser" version)) (sha256 (base32 "1qi4q3vijys4q1gfnflvvz8ws3j6f65rpprpgmrkqgiwfn7dvi6g")))) (properties `((upstream-name . "lefser"))) (build-system r-build-system) (propagated-inputs (list r-coin r-dplyr r-ggplot2 r-mass r-s4vectors r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://github.com/waldronlab/lefser") (synopsis "LEfSE method for microbiome biomarker discovery") (description "Lefser is an implementation in R of the popular \"LDA Effect Size\" (LEfSe) method for microbiome biomarker discovery. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers of groups and sub-groups.") (license license:artistic2.0))) (define-public r-lumi (package (name "r-lumi") (version "2.56.0") (source (origin (method url-fetch) (uri (bioconductor-uri "lumi" version)) (sha256 (base32 "04r7dw00yvjrxs0h6mwh79lwp55f5v8s4pgmzcy2fnpb2cdslpzy")))) (build-system r-build-system) (propagated-inputs (list r-affy r-annotate r-annotationdbi r-biobase r-dbi r-genomicfeatures r-genomicranges r-kernsmooth r-lattice r-mass r-methylumi r-mgcv r-nleqslv r-preprocesscore r-rsqlite)) (home-page "https://bioconductor.org/packages/lumi") (synopsis "BeadArray-specific methods for Illumina methylation and expression microarrays") (description "The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific 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 "2.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Linnorm" version)) (sha256 (base32 "1la6fwaap7957rrb4cs6w48kjz4hqrw3h39lpps419d4cbnsp5jz")))) (properties `((upstream-name . "Linnorm"))) (build-system r-build-system) (propagated-inputs (list r-amap r-apcluster r-ellipse r-fastcluster r-fpc r-ggdendro r-ggplot2 r-gmodels r-igraph r-limma r-mass r-mclust r-rcpp r-rcpparmadillo r-rtsne r-statmod r-vegan r-zoo)) (native-inputs (list r-knitr)) (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))) (define-public r-ioniser (package (name "r-ioniser") (version "2.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "IONiseR" version)) (sha256 (base32 "1ihski4akl70v6kq03di6w1pz63dx6rxgmyjkm0dv0nhgkmrza22")))) (properties `((upstream-name . "IONiseR"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biocparallel r-biostrings r-bit64 r-dplyr r-ggplot2 r-magrittr r-rhdf5 r-shortread r-stringr r-tibble r-tidyr r-xvector)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/IONiseR/") (synopsis "Quality assessment tools for Oxford Nanopore MinION data") (description "IONiseR provides tools for the quality assessment of Oxford Nanopore MinION data. It extracts summary statistics from a set of fast5 files and can be used either before or after base calling. In addition to standard summaries of the read-types produced, it provides a number of plots for visualising metrics relative to experiment run time or spatially over the surface of a flowcell.") (license license:expat))) ;; This is a CRAN package, but it depends on multtest from Bioconductor. (define-public r-mutoss (package (name "r-mutoss") (version "0.1-13") (source (origin (method url-fetch) (uri (cran-uri "mutoss" version)) (sha256 (base32 "0hgi9wpy3ai23dk6cdba6r118vvmgw210racsg3n1p24rv6ny3xn")))) (properties `((upstream-name . "mutoss"))) (build-system r-build-system) (propagated-inputs (list r-multcomp r-multtest r-mvtnorm r-plotrix)) (home-page "https://github.com/kornl/mutoss/") (synopsis "Unified multiple testing procedures") (description "This package is designed to ease the application and comparison of multiple hypothesis testing procedures for FWER, gFWER, FDR and FDX. Methods are standardized and usable by the accompanying mutossGUI package.") ;; Any version of the GPL. (license (list license:gpl2+ license:gpl3+)))) ;; This is a CRAN package, but it depends on mutoss, which depends on multtest ;; from Bioconductor, so we put it here. (define-public r-metap (package (name "r-metap") (version "1.10") (source (origin (method url-fetch) (uri (cran-uri "metap" version)) (sha256 (base32 "18l86026g5g0pdihw41h7yck1ad5k43bb7as5qih2k5xkr680mzx")))) (build-system r-build-system) (propagated-inputs (list r-lattice r-mathjaxr r-mutoss r-qqconf r-rdpack r-tfisher)) (home-page "http://www.dewey.myzen.co.uk/meta/meta.html") (synopsis "Meta-analysis of significance values") (description "The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display.") (license license:gpl2))) (define-public r-tradeseq (package (name "r-tradeseq") (version "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tradeSeq" version)) (sha256 (base32 "1kgvvvwvj3dgb2wik3y8j44ynda94bi05vvmiwlayrypqprwi1c1")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocparallel r-edger r-ggplot2 r-igraph r-magrittr r-mass r-matrix r-matrixstats r-mgcv r-pbapply r-princurve r-rcolorbrewer r-s4vectors r-singlecellexperiment r-slingshot r-summarizedexperiment r-tibble r-trajectoryutils r-viridis)) (native-inputs (list r-knitr)) (home-page "https://statomics.github.io/tradeSeq/index.html") (synopsis "Trajectory-based differential expression analysis") (description "This package provides a flexible method for fitting regression models that can be used to find genes that are differentially expressed along one or multiple lineages in a trajectory. Based on the fitted models, it uses a variety of tests suited to answer different questions of interest, e.g. the discovery of genes for which expression is associated with pseudotime, or which are differentially expressed (in a specific region) along the trajectory. It fits a negative binomial generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.") (license license:expat))) (define-public r-triform (package (name "r-triform") (version "1.29.0") (source (origin (method url-fetch) (uri (bioconductor-uri "triform" version)) (sha256 (base32 "089b7f6dwpi9abj0ncswbi4s30k45996zb99sh43avw6jcb6qj60")))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-iranges r-yaml)) (home-page "https://bioconductor.org/packages/triform/") (synopsis "Find enriched regions in transcription factor ChIP-sequencing data") (description "The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics.") (license license:gpl2))) (define-public r-varianttools (package (name "r-varianttools") (version "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "VariantTools" version)) (sha256 (base32 "1idil9vkd5risx9ahkagdacnj2g2a11gzsd7wmhg5gjmr77r53ww")))) (properties `((upstream-name . "VariantTools"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-biocparallel r-biostrings r-bsgenome r-genomeinfodb r-genomicfeatures r-genomicranges r-iranges r-matrix r-rsamtools r-rtracklayer r-s4vectors r-variantannotation)) (home-page "https://bioconductor.org/packages/VariantTools/") (synopsis "Tools for exploratory analysis of variant calls") (description "Explore, diagnose, and compare variant calls using filters. The VariantTools package supports a workflow for loading data, calling single sample variants and tumor-specific somatic mutations or other sample-specific variant types (e.g., RNA editing). Most of the functions operate on alignments (BAM files) or datasets of called variants. The user is expected to have already aligned the reads with a separate tool, e.g., GSNAP via gmapR.") (license license:artistic2.0))) (define-public r-heatplus (package (name "r-heatplus") (version "3.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Heatplus" version)) (sha256 (base32 "1pc63hk0smcflq4903hvs4pp8r0kzlx08j0m1kxlh14cxwppamyb")))) (properties `((upstream-name . "Heatplus"))) (build-system r-build-system) (propagated-inputs (list r-rcolorbrewer)) (home-page "https://github.com/alexploner/Heatplus") (synopsis "Heatmaps with row and/or column covariates and colored clusters") (description "This package provides tools to display a rectangular heatmap (intensity plot) of a data matrix. By default, both samples (columns) and features (row) of the matrix are sorted according to a hierarchical clustering, and the corresponding dendrogram is plotted. Optionally, panels with additional information about samples and features can be added to the plot.") (license license:gpl2+))) (define-public r-gosemsim (package (name "r-gosemsim") (version "2.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "GOSemSim" version)) (sha256 (base32 "0985w9b2iw7jbmpymfvqmpzshsy0lvqw7whc1djdnh58lwscnhcq")))) (properties `((upstream-name . "GOSemSim"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-go-db r-rcpp r-rlang r-yulab-utils)) (native-inputs (list r-knitr)) (home-page "https://guangchuangyu.github.io/software/GOSemSim") (synopsis "GO-terms semantic similarity measures") (description "The semantic comparisons of @dfn{Gene Ontology} (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters.") (license license:artistic2.0))) (define-public r-anota (package (name "r-anota") (version "1.52.0") (source (origin (method url-fetch) (uri (bioconductor-uri "anota" version)) (sha256 (base32 "1pg9p6982901k08iqpk0cdb9hii3k7bci9gq6an711r8a4iy3lmc")))) (build-system r-build-system) (propagated-inputs (list r-multtest r-qvalue)) (home-page "https://bioconductor.org/packages/anota/") (synopsis "Analysis of translational activity") (description "Genome wide studies of translational control is emerging as a tool to study various biological conditions. The output from such analysis is both the mRNA level (e.g. cytosolic mRNA level) and the level of mRNA actively involved in translation (the actively translating mRNA level) for each mRNA. The standard analysis of such data strives towards identifying differential translational between two or more sample classes - i.e., differences in actively translated mRNA levels that are independent of underlying differences in cytosolic mRNA levels. This package allows for such analysis using partial variances and the random variance model. As 10s of thousands of mRNAs are analyzed in parallel the library performs a number of tests to assure that the data set is suitable for such analysis.") (license license:gpl3))) (define-public r-anota2seq (package (name "r-anota2seq") (version "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "anota2seq" version)) (sha256 (base32 "140k37wswl4w2136pz9y0z82sphzxmgzgk3cr400kkm39wjn7vxm")))) (properties `((upstream-name . 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Analysis of translational efficiency aims to identify changes in translation efficiency leading to altered protein levels that are independent of total mRNA levels or buffering, a mechanism regulating translational efficiency so that protein levels remain constant despite fluctuating total mRNA levels.") (license license:gpl3))) (define-public r-fcscan (package (name "r-fcscan") (version "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "fcScan" version)) (sha256 (base32 "1gb15zrv44yn65wns7dk24rp54qv7wafqxgk1q8jnbkq9lp5wj2y")))) (properties `((upstream-name . 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(license license:artistic2.0))) (define-public r-fgsea (package (name "r-fgsea") (version "1.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "fgsea" version)) (sha256 (base32 "0nnvqsyrj24h5y8qw8llk9f4jgy0v734k37kcksfcpja17frdyjy")))) (build-system r-build-system) (propagated-inputs (list r-bh r-biocparallel r-cowplot r-data-table r-fastmatch r-ggplot2 r-matrix r-rcpp r-scales)) (native-inputs (list r-knitr)) (home-page "https://github.com/ctlab/fgsea/") (synopsis "Fast gene set enrichment analysis") (description "The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm makes more permutations and gets more fine grained p-values, which allows using accurate standard approaches to multiple hypothesis correction.") (license license:expat))) (define-public r-dose (package (name "r-dose") (version "3.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DOSE" version)) (sha256 (base32 "0hwbl3kcbjpjpdnqcq3ilk2qz3g87nybgv3kyd8fmh935jm66v6s")))) (properties `((upstream-name . "DOSE"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-biocparallel r-fgsea r-ggplot2 r-gosemsim r-hdo-db r-qvalue r-reshape2 r-yulab-utils)) (native-inputs (list r-knitr)) (home-page "https://guangchuangyu.github.io/software/DOSE/") (synopsis "Disease ontology semantic and enrichment analysis") (description "This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang, respectively, for measuring semantic similarities among @dfn{Disease ontology} (DO) terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.") 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This type of heatmap is just a normal heatmap but with some special settings, with the functionality of @code{ComplexHeatmap}, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondance between different data sources.") 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This allows the automation of such tasks using the R programming language and facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.") ;; Any version of the LGPL. (license license:lgpl2.1+))) (define-public r-yamss (package (name "r-yamss") (version "1.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "yamss" version)) (sha256 (base32 "0l9wqijwlq1gwybj2fy6jwgq6ja1mvx8yfdv174g5mjflx8nmc06")))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-data-table r-ebimage r-iranges r-limma r-matrix r-mzr r-s4vectors r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://github.com/hansenlab/yamss") (synopsis "Tools for high-throughput metabolomics") (description "This package provides tools to analyze and visualize high-throughput metabolomics data acquired using chromatography-mass spectrometry. 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(arguments `(#:phases (modify-phases %standard-phases (add-after 'unpack 'set-HOME (lambda _ (setenv "HOME" "/tmp")))))) (propagated-inputs (list r-dplyr r-igraph r-logger r-magrittr r-matrix r-omnipathr r-progress r-purrr r-rcurl r-rlang r-tibble r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://github.com/AnaGalhoz37/wppi") (synopsis "Weighting protein-protein interactions") (description "This package predicts functional relevance of protein-protein interactions based on functional annotations such as Human Protein Ontology and Gene Ontology, and prioritizes genes based on network topology, functional scores and a path search algorithm.") (license license:expat))) (define-public r-wrench (package (name "r-wrench") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Wrench" version)) (sha256 (base32 "1nwbqagpcs38c66r1arbby76if6pafa4snd6zbp18y71jj8rgvl7")))) (properties `((upstream-name . 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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 "1.44.0") (source (origin (method url-fetch) (uri (bioconductor-uri "QuasR" version)) (sha256 (base32 "116qnp7d7z4a56fv6n55yzrdlmma9gwrw234nmy8iapkn5ms3xky")))) (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 r-txdbmaker)) (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. 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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 "3.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "BiRewire" version)) (sha256 (base32 "1l3hkq6n7i9j82aym4ngwablj8jqb70a7y6skx0rjkflya6wbim7")))) (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.") 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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 "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MultiDataSet" version)) (sha256 (base32 "1y1j5svi52cvixjsn13122kvd0z0c7zfki3p6rr8wjd5w7riiyqw")))) (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. 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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).") 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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 "1.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "annotatr" version)) (sha256 (base32 "11cc3nknbckm0v5r7dzgqzw0137w4c08ab10s9svb1y02z45a0qz")))) (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 "2.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Rsubread" version)) (sha256 (base32 "0nd5b1k0dsxpf93wqx01fgbvk40jcfs7b7w692bsx620lm42ipfg")))) (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. 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"flowClust"))) (build-system r-build-system) (arguments `(#:configure-flags (list "--configure-args=--enable-bundled-gsl=no"))) (propagated-inputs (list r-biobase r-biocgenerics r-flowcore r-graph)) (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 "2.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "RProtoBufLib" version)) (sha256 (base32 "1vhp43l2iknljy240kzgvckkzbg186nkfdd1m3la9fnf9sqr33z9")))) (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-3.8.0.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 "4.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowWorkspace" version)) (sha256 (base32 "0k22hifg4sv0xiw983gf1d6y7zkn9072famwj72x47w8vag4i0xz")))) (properties `((upstream-name . "flowWorkspace"))) (build-system r-build-system) (propagated-inputs (list r-bh r-biobase r-biocgenerics r-cpp11 r-cytolib r-data-table r-delayedarray r-dplyr r-flowcore r-ggplot2 r-graph r-matrixstats r-ncdfflow r-rbgl 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 "4.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowStats" version)) (sha256 (base32 "0q8g3sqmbhinfrb63yhv4lsczjz7pqwhwwsdlz2cg7s8yhp0cj6v")))) (properties `((upstream-name . "flowStats"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-clue r-cluster r-corpcor r-fda r-flowcore r-flowviz r-flowworkspace r-kernsmooth r-ks r-lattice r-mass r-mnormt 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 "2.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "openCyto" version)) (sha256 (base32 "08dn7k3jlicj755rwhpw48fmi9via79vd34imaffwdzq3aldi83m")))) (properties `((upstream-name . "openCyto"))) (build-system r-build-system) (propagated-inputs (list r-bh r-biobase r-biocgenerics r-cpp11 r-data-table r-flowclust r-flowcore r-flowviz r-flowworkspace r-graph r-ncdfflow r-rbgl r-rcolorbrewer)) (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 "2.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "CytoML" version)) (sha256 (base32 "11kflx3yahl7xjl6x2rgpd4hl5y69qgarzhalmz4qdci7b7ln7kr")))) (properties `((upstream-name . "CytoML"))) (build-system r-build-system) (inputs (list libxml2)) (propagated-inputs (list r-bh r-biobase r-cpp11 r-cytolib r-data-table r-dplyr r-flowcore r-flowworkspace r-ggcyto r-graph r-jsonlite r-opencyto r-rbgl r-rgraphviz r-rhdf5lib r-rprotobuflib r-tibble r-xml 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 "2.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "FlowSOM" version)) (sha256 (base32 "0xqrp184p00pvzzf6ddmp2r8lpg97bm0q6smjwcrfb8rn4msxmis")))) (properties `((upstream-name . "FlowSOM"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-colorramps r-consensusclusterplus r-dplyr r-flowcore r-ggforce r-ggnewscale r-ggplot2 r-ggpubr r-igraph r-magrittr r-rlang r-rtsne 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 "6.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mixOmics" version)) (sha256 (base32 "03pdg2hz4wnyigqakb9098ak9ww8fhwypzn006hfad0s042p9wvj")))) (properties `((upstream-name . "mixOmics"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-corpcor r-dplyr r-ellipse r-ggplot2 r-ggrepel 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 "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DepecheR" version)) (sha256 (base32 "15lpn1p2p28lhmzi7svszr0p1zkyaivi69q8pxcrv4lvips38hk4")))) (properties `((upstream-name . "DepecheR"))) (build-system r-build-system) (propagated-inputs (list r-beanplot r-clusterr r-collapse 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 "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "RcisTarget" version)) (sha256 (base32 "1856jnvqacr12j5hnnl4w2abjjd7qvkz7cs8yhbnqpy1896wki0v")))) (properties `((upstream-name . "RcisTarget"))) (build-system r-build-system) (propagated-inputs (list r-arrow r-aucell r-biocgenerics r-data-table r-dplyr r-genomeinfodb r-genomicranges r-gseabase r-r-utils r-s4vectors r-summarizedexperiment r-tibble r-zoo)) (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 "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Chicago" version)) (sha256 (base32 "05djywxsyfxb26d0clx51q7wmsw3rq56va444d6iy5n7xlhj9m94")))) (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))) ;; This is a CRAN package, but it depends on Bioconductor packages, so we put ;; it here. (define-public r-ciara (package (name "r-ciara") (version "0.1.0") (source (origin (method url-fetch) (uri (cran-uri "CIARA" version)) (sha256 (base32 "0nr7wks9231326x0lhpbh824c6vcb5hr5jn89s9bmg9mci907bsf")))) (properties `((upstream-name . "CIARA"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-ggplot2 r-ggraph r-magrittr)) (native-inputs (list r-knitr)) (home-page "https://cran.r-project.org/package=CIARA") (synopsis "Cluster-independent algorithm for rare cell types identification") (description "This is a package to support identification of markers of rare cell types by looking at genes whose expression is confined in small regions of the expression space.") (license license:artistic2.0))) (define-public r-cicero (package (name "r-cicero") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "cicero" version)) (sha256 (base32 "0x5ly5hkqli5b67hiaa6ha02damyps7vb4l51p0az1j5fxl39n8r")))) (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 "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "circRNAprofiler" version)) (sha256 (base32 "0gjnx4645kd7qag7dzs5dp9lhsv6zg5xn6jna3bap4mginl1jvxi")))) (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 "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "GENIE3" version)) (sha256 (base32 "0ijwyx42saqas52273c63c3yi948bh4pd4lifyqi3zjjs17bj1cg")))) (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.") (license license:gpl2+))) (define-public r-roc (package (name "r-roc") (version "1.80.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ROC" version)) (sha256 (base32 "074c6jg0dyr3hckizpg56f8ij8szj43cx6x5bbw7a01xdjdc70yb")))) (properties `((upstream-name . "ROC"))) (build-system r-build-system) (native-inputs (list r-knitr)) (home-page "https://www.bioconductor.org/packages/ROC/") (synopsis "Utilities for ROC curves") (description "This package provides utilities for @dfn{Receiver Operating Characteristic} (ROC) curves, with a focus on micro arrays.") (license license:artistic2.0))) (define-public r-watermelon (package (name "r-watermelon") (version "2.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "wateRmelon" version)) (sha256 (base32 "19zlv9aglllsjq3jcnlw994bkanjdq0ib46k7wjsig04cx4apz1v")))) (properties `((upstream-name . "wateRmelon"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-illuminahumanmethylation450kanno-ilmn12-hg19 r-illuminaio r-limma r-lumi r-matrixstats r-methylumi r-roc)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/wateRmelon/") (synopsis "Illumina 450 methylation array normalization and metrics") (description "The standard index of DNA methylation (beta) is computed from methylated and unmethylated signal intensities. Betas calculated from raw signal intensities perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. This package provides 15 flavours of betas and three performance metrics, with methods for objects produced by the @code{methylumi} and @code{minfi} packages.") (license license:gpl3))) (define-public r-gdsfmt (package (name "r-gdsfmt") (version "1.40.0") (source (origin (method url-fetch) (uri (bioconductor-uri "gdsfmt" version)) (sha256 (base32 "1ska6q1800mmsxi6jilpnq4f6cy3vk0nb98gz3ik94lmbv2ram97")) (modules '((guix build utils))) ;; Remove bundled sources of zlib, lz4, and xz. Don't attempt to build ;; them and link with system libraries instead. (snippet '(begin (for-each delete-file-recursively '("src/LZ4" "src/XZ" "src/ZLIB")) (substitute* "src/Makevars" (("all: \\$\\(SHLIB\\)") "all:") (("\\$\\(SHLIB\\): liblzma.a") "") (("^ (ZLIB|LZ4)/.*") "") (("CoreArray/dVLIntGDS.cpp.*") "CoreArray/dVLIntGDS.cpp") (("CoreArray/dVLIntGDS.o.*") "CoreArray/dVLIntGDS.o") (("PKG_LIBS = ./liblzma.a") "PKG_LIBS = -llz4")) (substitute* "src/CoreArray/dStream.h" (("include \"../(ZLIB|LZ4|XZ/api)/(.*)\"" _ _ header) (string-append "include <" header ">"))))))) (properties `((upstream-name . "gdsfmt") (updater-extra-inputs . ("lz4" "xz" "zlib")))) (build-system r-build-system) (inputs (list lz4 xz zlib)) (native-inputs (list r-knitr)) (home-page "http://corearray.sourceforge.net/") (synopsis "R Interface to CoreArray Genomic Data Structure (GDS) Files") (description "This package provides a high-level R interface to CoreArray @dfn{Genomic Data Structure} (GDS) data files, which are portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited for large-scale datasets, especially for data which are much larger than the available random-access memory. The @code{gdsfmt} package offers efficient operations specifically designed for integers of less than 8 bits, since a diploid genotype, like @dfn{single-nucleotide polymorphism} (SNP), usually occupies fewer bits than a byte. Data compression and decompression are available with relatively efficient random access. It is also allowed to read a GDS file in parallel with multiple R processes supported by the package @code{parallel}.") (license license:lgpl3))) (define-public r-bigmelon (package (name "r-bigmelon") (version "1.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "bigmelon" version)) (sha256 (base32 "0fa1dwbk6hdiwg6dmbks7hy4cg3ydyd2sv94cyl0003awhf00nn9")))) (properties `((upstream-name . "bigmelon"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-gdsfmt r-geoquery r-illuminaio r-methylumi r-minfi r-watermelon)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/bigmelon/") (synopsis "Illumina methylation array analysis for large experiments") (description "This package provides methods for working with Illumina arrays using the @code{gdsfmt} package.") (license license:gpl3))) (define-public r-seqbias (package (name "r-seqbias") (version "1.50.0") (source (origin (method url-fetch) (uri (bioconductor-uri "seqbias" version)) (sha256 (base32 "18pdpi855y1hhka96xc5886nqffjn1jhz9jr9p305iikdrsvmjp1")))) (properties `((upstream-name . "seqbias"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-genomicranges r-rhtslib r-zlibbioc)) (home-page "https://bioconductor.org/packages/seqbias/") (synopsis "Estimation of per-position bias in high-throughput sequencing data") (description "This package implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence.") 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In addition, the package integrates RNA-Seq data to estimate the False Discovery Rate of cluster detection. Key functions support parallel multicore computing. While wavClusteR was designed for PAR-CLIP data analysis, it can be applied to the analysis of other NGS data obtained from experimental procedures that induce nucleotide substitutions (e.g. BisSeq).") (license license:gpl2))) (define-public r-tilingarray (package (name "r-tilingarray") (version "1.82.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tilingArray" version)) (sha256 (base32 "1408275gvfilc2k8sfsja8bm5fdgnblf2sf5wdd3if51qi61clb0")))) (properties `((upstream-name . 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(license license:gpl3))) ;; This is a CRAN package, but it depends on Bioconductor packages, so we put ;; it here. (define-public r-activedriverwgs (package (name "r-activedriverwgs") (version "1.2.0") (source (origin (method url-fetch) (uri (cran-uri "ActiveDriverWGS" version)) (sha256 (base32 "0xnplgwxd197a4d422bsxg753q158i12ils16awd1cw30wafdxkk")))) (properties `((upstream-name . "ActiveDriverWGS"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-bsgenome r-bsgenome-hsapiens-ucsc-hg19 r-bsgenome-hsapiens-ucsc-hg38 r-bsgenome-mmusculus-ucsc-mm9 r-bsgenome-mmusculus-ucsc-mm10 r-genomeinfodb r-genomicranges r-iranges r-s4vectors)) (native-inputs (list r-knitr)) (home-page "https://cran.r-project.org/web/packages/ActiveDriverWGS/") (synopsis "Driver discovery tool for cancer whole genomes") (description "This package provides a method for finding an enrichment of cancer simple somatic mutations (SNVs and Indels) in functional elements across the human genome. 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To reduce the chances ;;; of a merge conflict, place them above by existing packages with similar ;;; functionality or similar names. ;;;