;;; GNU Guix --- Functional package management for GNU ;;; Copyright © 2015-2023 Ricardo Wurmus ;;; Copyright © 2016, 2017, 2018, 2020, 2021 Roel Janssen ;;; Copyright © 2016 Pjotr Prins ;;; Copyright © 2016 Ben Woodcroft ;;; Copyright © 2017, 2022 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 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 netpbm) #:use-module (gnu packages python) #:use-module (gnu packages perl) #:use-module (gnu packages pkg-config) #: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-hpo-db (package (name "r-hpo-db") (version "0.99.2") (source (origin (method url-fetch) (uri (bioconductor-uri "HPO.db" version 'annotation)) (sha256 (base32 "1brzrnafvyh76h8a663gk5lprhixxpi9xi65vwgxwf7jh6yw0was")))) (properties `((upstream-name . 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The study of model organisms can be transformed into useful knowledge about normal human biology and disease to facilitate treatment and early screening for diseases. Organism-specific genotype-phenotypic associations can be applied to cross-species phenotypic studies to clarify previously unknown phenotypic connections in other species. Using the same principle to diseases can identify genetic associations and even help to identify disease associations that are not obvious.") (license license:artistic2.0))) (define-public r-org-eck12-eg-db (package (name "r-org-eck12-eg-db") (version "3.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "org.EcK12.eg.db" version 'annotation)) (sha256 (base32 "0c4p6jr83k0gm6pvn760yr8xf33wggrfcr6fg7a42a96bcf817gs")))) (properties `((upstream-name . 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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 "1.72.0") (source (origin (method url-fetch) (uri (bioconductor-uri "adSplit" version)) (sha256 (base32 "0av0kji4r788cn5808g13svqpydq6xk4d2awpzpsckz7xbjyx0ya")))) (properties `((upstream-name . 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ASpli is an integrative pipeline and user-friendly R package that facilitates the analysis of changes in both annotated and novel AS events. ASpli integrates several independent signals in order to deal with the complexity that might arise in splicing patterns.") ;; The authors didn't specify any GPL version in description or in the ;; sources. (license (list license:gpl2+ license:gpl3+)))) (define-public r-assessorf (package (name "r-assessorf") (version "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "AssessORF" version)) (sha256 (base32 "16nv6sh7z3l6ff3a7zrixkc04mhrak38q045xlirgljkcragz1c5")))) (properties `((upstream-name . 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Parameters are inferred via @dfn{MCMC} (Markov chain Monte Carlo) techniques and a DTU test is performed via a multivariate Wald test on the posterior densities for the average relative abundance of transcripts.") (license license:gpl3+))) (define-public r-banocc (package (name "r-banocc") (version "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "banocc" version)) (sha256 (base32 "0yi70y87isb34jc1wrnz4gr0d0f2zw44555s50j3qdnj1x8cld9y")))) (properties `((upstream-name . "banocc"))) (build-system r-build-system) (propagated-inputs (list r-coda r-mvtnorm r-rstan r-stringr)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/banocc") (synopsis "Bayesian analysis of compositional covariance") (description "BAnOCC is a package designed for compositional data, where each sample sums to one. It infers the approximate covariance of the unconstrained data using a Bayesian model coded with @code{rstan}. It provides as output the @code{stanfit} object as well as posterior median and credible interval estimates for each correlation element.") (license license:expat))) (define-public r-barcodetrackr (package (name "r-barcodetrackr") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "barcodetrackR" version)) (sha256 (base32 "155lxqqq2mgrz9i04xvv8y7gh2iacw6qd3mzijzbvrbm605qb3p8")))) (properties `((upstream-name . "barcodetrackR"))) (build-system r-build-system) (propagated-inputs (list r-circlize r-cowplot r-dplyr r-ggdendro r-ggplot2 r-ggridges r-magrittr r-plyr r-proxy r-rcolorbrewer r-rlang r-s4vectors r-scales r-shiny r-summarizedexperiment r-tibble r-tidyr r-vegan r-viridis)) (native-inputs (list r-knitr)) (home-page "https://github.com/dunbarlabNIH/barcodetrackR") (synopsis "Functions for analyzing cellular barcoding data") (description "This package is developed for the analysis and visualization of clonal tracking data. 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(license license:gpl2+))) (define-public r-damefinder (package (name "r-damefinder") (version "1.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DAMEfinder" version)) (sha256 (base32 "0m8g1sp55mxa0qswpqkzk73myhhy3s49c21hf97sk0lxis5lagcd")))) (properties `((upstream-name . "DAMEfinder"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biostrings r-bumphunter r-cowplot r-genomeinfodb r-genomicalignments r-genomicranges r-ggplot2 r-iranges r-limma r-plyr r-readr r-reshape2 r-rsamtools r-s4vectors r-stringr r-summarizedexperiment r-variantannotation)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/DAMEfinder") (synopsis "Differential allelicly methylated regions") (description "This package offers functionality for taking methtuple or Bismark outputs to calculate @acronym{ASM, Allele-Specific Methylation} scores and compute @acronym{DAMEs, Differential Allelicly MEthylated} regions. 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(license license:gpl2))) (define-public r-debcam (package (name "r-debcam") (version "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "debCAM" version)) (sha256 (base32 "1swqqrlwin2i2qq46qyfziblbfsfyd5hf6w39hygp7fdkpic14b7")) (snippet '(for-each delete-file '("inst/java/CornerDetect.jar" "inst/java/lib/pj20150107.jar"))))) (properties `((upstream-name . 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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 "2.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DECIPHER" version)) (sha256 (base32 "16z6yk8rr2115z6g1l7fl01binxm29vnxsnsm2wzfvc5vv49927n")))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-dbi r-iranges r-rsqlite 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 "2.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "decompTumor2Sig" version)) (sha256 (base32 "028sczy1d108i05ymr1wpj6jdrcds476wbmmc7rzzflzyg4aix75")))) (properties `((upstream-name . 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(license license:gpl2))) (define-public r-deconrnaseq (package (name "r-deconrnaseq") (version "1.42.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DeconRNASeq" version)) (sha256 (base32 "0bmkyci31p7g097i8fvc0s1fz47hv6vp5rcfqqkvclm86wfkkmkc")))) (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 "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "decontam" version)) (sha256 (base32 "08niwixy4m6gqmazisxzbbla9nsxicpa685jy3r6knapwaznvcb2")))) (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 "1.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "deconvR" version)) (sha256 (base32 "1r5js5prwy1libnf1g1a4pdi15pj216bb8ajhzii3symn5r0cdj9")))) (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 "2.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "decoupleR" version)) (sha256 (base32 "012d76jwgg6fwfjc00zdws59y6jbj0grzd4lgjrqs2afp2ycmh9s")))) (properties `((upstream-name . 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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 "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "deepSNV" version)) (sha256 (base32 "11cnyy3hyn8akhmax25293mx2blcs8ba5vfax6mx6hjhb577hkwb")))) (properties `((upstream-name . "deepSNV"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-genomicranges r-iranges r-rhtslib r-summarizedexperiment r-variantannotation r-vgam)) (native-inputs (list r-knitr)) (home-page "https://github.com/gerstung-lab/deepSNV/") (synopsis "Detection of subclonal SNVs in deep sequencing data") (description "This package provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs. The shearwater algorithm computes a Bayes classifier based on a beta-binomial model for variant calling with multiple samples for precisely estimating model parameters - such as local error rates and dispersion - and prior knowledge, e.g. from variation data bases such as COSMIC.") (license license:gpl3))) (define-public r-degreport (package (name "r-degreport") (version "1.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DEGreport" version)) (sha256 (base32 "15xm1l2qgsyzaw820a1fq5qdzh5pj4dmr1hx6s6b6wm2p02cvvai")) (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 "0.26.7") (source (origin (method url-fetch) (uri (bioconductor-uri "DelayedArray" version)) (sha256 (base32 "1xsq85nm1gk537mw6ppsyykpw70kczv6wn1nll63b0k8xs4wj0ha")))) (properties `((upstream-name . "DelayedArray"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-iranges r-matrix r-matrixgenerics r-s4arrays r-s4vectors)) (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 "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "derfinder" version)) (sha256 (base32 "1gb65hk26ffn0njsgwgk43z9i9bcvx89pz5m9x951c2a07c1xrcw")))) (properties `((upstream-name . 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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 "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DRIMSeq" version)) (sha256 (base32 "1i9lcp31g94mllkwcyfablj27qr8v7vqk9j96ywrdfpj8dmcrw98")))) (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. 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(license license:gpl3))) (define-public r-mutationalpatterns (package (name "r-mutationalpatterns") (version "3.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MutationalPatterns" version)) (sha256 (base32 "1p9n5afnr4cx690w9d5q1hkwqffsbnsn72wibqcl5rbqgfsvhf8h")))) (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.") 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This type of data, however, is more challenging to interpret and less common practice compared to mRNA-seq. One of the challenges for primary transcript detection concerns the simultaneous transcription of closely spaced genes, which needs to be properly divided into individually transcribed units. The R package transcriptR combines RNA-seq data with ChIP-seq data of histone modifications that mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this challenge. The advantage of this approach over the use of, for example, gene annotations is that this approach is data driven and therefore able to deal also with novel and case specific events.") (license license:gpl3))) (define-public r-trajectoryutils (package (name "r-trajectoryutils") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "TrajectoryUtils" version)) (sha256 (base32 "1q3c226fskl45gq28xj2w5paz2s9n9kxm0bkkgg0329w399cs09k")))) (properties `((upstream-name . 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It is flexible enough to handle arbitrarily many branching events and allows for the incorporation of prior knowledge through supervised graph construction.") (license license:artistic2.0))) ;; This is a CRAN package but it depends on a bioconductor package. (define-public r-speaq (package (name "r-speaq") (version "2.7.0") (source (origin (method url-fetch) (uri (cran-uri "speaq" version)) (sha256 (base32 "0z9a3nbfazphp090c6hg892vjq7jp4g4cij3s5wbs1q567inbmlk")))) (properties `((upstream-name . "speaq"))) (build-system r-build-system) (propagated-inputs (list r-cluster r-data-table r-dosnow r-foreach r-ggplot2 r-gridextra r-impute r-massspecwavelet r-missforest r-reshape2 r-rfast r-rvest r-xml2)) (native-inputs (list r-knitr)) (home-page "https://cran.r-project.org/package=speaq") (synopsis "Tools for nuclear magnetic resonance spectra alignment") (description "This package aims to make @acronym{NMR, Nuclear Magnetic Resonance} spectroscopy data analysis as easy as possible. 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Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.") ;; Any version of the LGPL applies. (license license:lgpl2.1+))) (define-public r-tximport (package (name "r-tximport") (version "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tximport" version)) (sha256 (base32 "0km1vfn4jcp05jk5srrqanjngq6ghh5im6h1c424b926g9s7w7k1")))) (build-system r-build-system) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/tximport") (synopsis "Import and summarize transcript-level estimates for gene-level analysis") (description "This package provides tools to import transcript-level abundance, estimated counts and transcript lengths, and to summarize them into matrices for use with downstream gene-level analysis packages. 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This allows us to naturally represent multivariate data in a format that is compatible with two-dimensional containers like the @code{SummarizedExperiment} and @code{MultiAssayExperiment} objects.") (license license:expat))) (define-public r-mia (package (name "r-mia") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mia" version)) (sha256 (base32 "1p78yacx0cgihva7m2n3vnll5w4b47vl98hy12pq9rnmhk6r591z")))) (properties `((upstream-name . 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(license license:artistic2.0))) (define-public r-microbiome (package (name "r-microbiome") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "microbiome" version)) (sha256 (base32 "120wyjv2r9cbjgxbp70nzf249hai8cqn59gcbgwnazynfy5ih1w8")))) (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 "1.1") (source (origin (method url-fetch) (uri (cran-uri "MicrobiomeStat" version)) (sha256 (base32 "1j5sar85a1gksc83pc4ypxwb0c7whxglx069zarphrgqfazcr1m4")))) (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-matrixstats r-patchwork r-rcolorbrewer 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 "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "minfi" version)) (sha256 (base32 "18b9yg9hnnm1saaiprm2hj86aajjwm1zwvpj0yadfa3s811pw4nq")))) (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 "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "missMethyl" version)) (sha256 (base32 "1jvrdr57mv93pcbyazcg1bcx1zd0kp72hi1if839gw54hk3igs3h")))) (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 "2.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "methylumi" version)) (sha256 (base32 "1aa0pwjyp2p9a4mx4n4qw88ndgrj56p669yzdkd7hxhc3x55nzlf")))) (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 "1.10.1") (source (origin (method url-fetch) (uri (bioconductor-uri "lefser" version)) (sha256 (base32 "1ifmbbsbyzcyvjni9ww27c9qsqliv7vj2rv9mg9c7gnqgbg6h2c4")))) (properties `((upstream-name . 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(license license:artistic2.0))) (define-public r-lumi (package (name "r-lumi") (version "2.52.0") (source (origin (method url-fetch) (uri (bioconductor-uri "lumi" version)) (sha256 (base32 "1lxxqr7x9jdjrsj5j95jb0dbd7p208vifxw3j4s4140zh1ppxnpj")))) (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 "2.24.1") (source (origin (method url-fetch) (uri (bioconductor-uri "Linnorm" version)) (sha256 (base32 "1sqkmjah2lxahnvwv04a970za2b8kzvmxnb41k9xrnvj0akigc2d")))) (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 "2.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "IONiseR" version)) (sha256 (base32 "1yrsd5n9zam6wslc6savfn122v3wzzcc46w20mb849qq2np4frf0")))) (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 "1.9") (source (origin (method url-fetch) (uri (cran-uri "metap" version)) (sha256 (base32 "1w4mv7vb94d4pkllvabz9az8sbrbfhigxw4is3j0jzi1pnlyc8kg")))) (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 "1.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tradeSeq" version)) (sha256 (base32 "14b90x9h34mhbc4sdpzkygrrswf84pi1ddwpzxhvlvr9gs443xqs")))) (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 "1.42.0") (source (origin (method url-fetch) (uri (bioconductor-uri "VariantTools" version)) (sha256 (base32 "1vkdw626r1ffdsvry6qwhd1i3lkyb9wzrp9zf3dfafi02cap6r47")))) (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 "3.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Heatplus" version)) (sha256 (base32 "031f25w960jp5nhd78v3iv6pib266cpbawhi9rrd7csw89vnswfx")))) (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 "2.26.1") (source (origin (method url-fetch) (uri (bioconductor-uri "GOSemSim" version)) (sha256 (base32 "15z7wqnp0s8fiysl3qc76pjaj3xik2br2mz2z3nmf28vxig69mx9")))) (properties `((upstream-name . "GOSemSim"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-go-db r-rcpp)) (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 "1.48.0") (source (origin (method url-fetch) (uri (bioconductor-uri "anota" version)) (sha256 (base32 "0ic12p1qyfrmh3l1wv7s9yi8sr84crj4nksmcx0lybb6rak9gy0x")))) (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 "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "anota2seq" version)) (sha256 (base32 "0pmk45276bl3qppzxlp4jpc8bsvdpca8nzrdl6c4n9r3xhzfpyq0")))) (properties `((upstream-name . 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GOfuncR provides the standard candidate vs background enrichment analysis using the hypergeometric test, as well as three additional tests: @enumerate @item the Wilcoxon rank-sum test that is used when genes are ranked, @item a binomial test that is used when genes are associated with two counts, and @item a Chi-square or Fisher's exact test that is used in cases when genes are associated with four counts. @end enumerate To correct for multiple testing and interdependency of the tests, family-wise error rates are computed based on random permutations of the gene-associated variables. GOfuncR also provides tools for exploring the ontology graph and the annotations, and options to take gene-length or spatial clustering of genes into account. It is also possible to provide custom gene coordinates, annotations and ontologies.") (license license:gpl2+))) (define-public r-abaenrichment (package (name "r-abaenrichment") (version "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ABAEnrichment" version)) (sha256 (base32 "1sp3f72rzlr822dxx42bswynrwwfx6f520hdhfdikqp13p2y4044")))) (properties `((upstream-name . "ABAEnrichment"))) (build-system r-build-system) (propagated-inputs (list r-abadata r-data-table r-gofuncr r-gplots r-gtools r-rcpp)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/ABAEnrichment/") (synopsis "Gene expression enrichment in human brain regions") (description "The package ABAEnrichment is designed to test for enrichment of user defined candidate genes in the set of expressed genes in different human brain regions. The core function @code{aba_enrich} integrates the expression of the candidate gene set (averaged across donors) and the structural information of the brain using an ontology, both provided by the Allen Brain Atlas project.") (license license:gpl2+))) (define-public r-annotationfuncs (package (name "r-annotationfuncs") (version "1.40.0") (source (origin (method url-fetch) (uri (bioconductor-uri "AnnotationFuncs" version)) (sha256 (base32 "0xsm7741zm81bi4c9hy0zaacnk8a6bahdpc6srqzrbsz0pfzdyhr")))) (properties `((upstream-name . "AnnotationFuncs"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-dbi)) (home-page "https://www.iysik.com/r/annotationfuncs") (synopsis "Annotation translation functions") (description "This package provides functions for handling translating between different identifieres using the Biocore Data Team data-packages (e.g. @code{org.Bt.eg.db}).") (license license:gpl2))) (define-public r-annotationtools (package (name "r-annotationtools") (version "1.74.0") (source (origin (method url-fetch) (uri (bioconductor-uri "annotationTools" version)) (sha256 (base32 "0dwbh2h2mp8gy0kwqmkri3q2glnzcj8cn83j1qyh7lk15anc33g8")))) (properties `((upstream-name . 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In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.") (license license:gpl3))) (define-public r-ebimage (package (name "r-ebimage") (version "4.42.0") (source (origin (method url-fetch) (uri (bioconductor-uri "EBImage" version)) (sha256 (base32 "0z0ajmy1zx7mqcjm2ibyk2qg3cj00kl76padyksbdbmwdncxs8yb")))) (properties `((upstream-name . "EBImage"))) (build-system r-build-system) (propagated-inputs (list r-abind r-biocgenerics r-fftwtools r-htmltools r-htmlwidgets r-jpeg r-locfit r-png r-rcurl r-tiff)) (native-inputs (list r-knitr)) ; for vignettes (home-page "https://github.com/aoles/EBImage") (synopsis "Image processing and analysis toolbox for R") (description "EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. 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 "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "yamss" version)) (sha256 (base32 "0kjlp62s2393jdwp0crizsgp4iqagbgnd3hdl9vpbr9qrjxg4s7m")))) (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. These tools preprocess data in a way that enables reliable and powerful differential analysis.") (license license:artistic2.0))) (define-public r-gtrellis (package (name "r-gtrellis") (version "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "gtrellis" version)) (sha256 (base32 "1kk7ysscq8xdbn35b20s8sn8gl93sy0c718fmvr1yrhiqaxq5alr")))) (build-system r-build-system) (propagated-inputs (list r-circlize r-genomicranges r-getoptlong r-iranges)) (native-inputs (list r-knitr)) (home-page "https://github.com/jokergoo/gtrellis") (synopsis "Genome level Trellis layout") (description "Genome level Trellis graph visualizes genomic data conditioned by genomic categories (e.g. chromosomes). For each genomic category, multiple dimensional data which are represented as tracks describe different features from different aspects. This package provides high flexibility to arrange genomic categories and to add self-defined graphics in the plot.") (license license:expat))) (define-public r-somaticsignatures (package (name "r-somaticsignatures") (version "2.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "SomaticSignatures" version)) (sha256 (base32 "075w88x7lv2fkp2ipqgxp4pzh6kbjw3nmp0qra2p4fss4j3g8d6s")))) (properties `((upstream-name . "SomaticSignatures"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biostrings r-genomeinfodb r-genomicranges r-ggbio r-ggplot2 r-iranges r-nmf r-pcamethods r-proxy r-reshape2 r-s4vectors r-variantannotation)) (native-inputs (list r-knitr)) (home-page "https://github.com/juliangehring/SomaticSignatures") (synopsis "Somatic signatures") (description "This package identifies mutational signatures of @dfn{single nucleotide variants} (SNVs). It provides a infrastructure related to the methodology described in Nik-Zainal (2012, Cell), with flexibility in the matrix decomposition algorithms.") (license license:expat))) (define-public r-yapsa (package (name "r-yapsa") (version "1.26.8") (source (origin (method url-fetch) (uri (bioconductor-uri "YAPSA" version)) (sha256 (base32 "16rr2bkni3jx5qskr5fz5lvf23d03xgd3m4068mnd3n9r23hpb4p")))) (properties `((upstream-name . "YAPSA"))) (build-system r-build-system) (propagated-inputs (list r-biostrings r-bsgenome-hsapiens-ucsc-hg19 r-circlize r-complexheatmap r-corrplot r-dendextend r-doparallel r-dplyr r-genomeinfodb r-genomicranges r-getoptlong r-ggbeeswarm r-ggplot2 r-gridextra r-gtrellis r-keggrest r-limsolve r-magrittr r-pmcmrplus r-pracma r-reshape2 r-somaticsignatures r-variantannotation)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/YAPSA/") (synopsis "Yet another package for signature analysis") (description "This package provides functions and routines useful in the analysis of somatic signatures (cf. L. Alexandrov et al., Nature 2013). In particular, functions to perform a signature analysis with known signatures and a signature analysis on @dfn{stratified mutational catalogue} (SMC) are provided.") (license license:gpl3))) (define-public r-gcrma (package (name "r-gcrma") (version "2.72.0") (source (origin (method url-fetch) (uri (bioconductor-uri "gcrma" version)) (sha256 (base32 "0k4fsmqkv82d3a6v3gwphvbri5sgbd3f1s4qyv960rhyk2xj2b4p")))) (build-system r-build-system) (propagated-inputs (list r-affy r-affyio r-biobase r-biocmanager r-biostrings r-xvector)) (home-page "https://bioconductor.org/packages/gcrma/") (synopsis "Background adjustment using sequence information") (description "Gcrma adjusts for background intensities in Affymetrix array data which include optical noise and @dfn{non-specific binding} (NSB). The main function @code{gcrma} converts background adjusted probe intensities to expression measures using the same normalization and summarization methods as a @dfn{Robust Multiarray Average} (RMA). Gcrma uses probe sequence information to estimate probe affinity to NSB. The sequence information is summarized in a more complex way than the simple GC content. Instead, the base types (A, T, G or C) at each position along the probe determine the affinity of each probe. The parameters of the position-specific base contributions to the probe affinity is estimated in an NSB experiment in which only NSB but no gene-specific binding is expected.") ;; Any version of the LGPL (license license:lgpl2.1+))) (define-public r-simpleaffy (package (name "r-simpleaffy") (version "2.66.0") (source (origin (method url-fetch) (uri (bioconductor-uri "simpleaffy" version)) (sha256 (base32 "04a11dsqd5y4b39nny94acnh0qhdazjc6d1803izza4vrgmw2csb")))) (build-system r-build-system) (propagated-inputs (list r-affy r-biobase r-biocgenerics r-gcrma r-genefilter)) (home-page "https://bioconductor.org/packages/simpleaffy/") (synopsis "Very simple high level analysis of Affymetrix data") (description "This package provides high level functions for reading Affy @file{.CEL} files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. It makes heavy use of the @code{affy} library. It also has some basic scatter plot functions and mechanisms for generating high resolution journal figures.") (license license:gpl2+))) (define-public r-yaqcaffy (package (name "r-yaqcaffy") (version "1.50.0") (source (origin (method url-fetch) (uri (bioconductor-uri "yaqcaffy" version)) (sha256 (base32 "18gphcjj15iivrahp52186bvdg07yd2dvrykfjdd4r1vyf33im96")))) (build-system r-build-system) (propagated-inputs (list r-simpleaffy)) (home-page "https://bioconductor.org/packages/yaqcaffy/") (synopsis "Affymetrix quality control and reproducibility analysis") (description "This is a package that can be used for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.") (license license:artistic2.0))) (define-public r-quantro (package (name "r-quantro") (version "1.34.0") (source (origin (method url-fetch) (uri (bioconductor-uri "quantro" version)) (sha256 (base32 "08m94q65c11isbkx9xljm2bx2aq2rml1bqh5i1cg81xg2ilm9h6a")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-doparallel r-foreach r-ggplot2 r-iterators r-minfi r-rcolorbrewer)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/quantro/") (synopsis "Test for when to use quantile normalization") (description "This package provides a data-driven test for the assumptions of quantile normalization using raw data such as objects that inherit eSets (e.g. ExpressionSet, MethylSet). Group level information about each sample (such as Tumor / Normal status) must also be provided because the test assesses if there are global differences in the distributions between the user-defined groups.") (license license:gpl3+))) (define-public r-yarn (package (name "r-yarn") (version "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "yarn" version)) (sha256 (base32 "0ddfl4jp0n8sb665hcpsij959fl28rj22n1h61wp2374kpc0fwfj")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biomart r-downloader r-edger r-gplots r-limma r-matrixstats r-preprocesscore r-quantro r-rcolorbrewer r-readr)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/yarn/") (synopsis "Robust multi-condition RNA-Seq preprocessing and normalization") (description "Expedite large RNA-Seq analyses using a combination of previously developed tools. YARN is meant to make it easier for the user in performing basic mis-annotation quality control, filtering, and condition-aware normalization. YARN leverages many Bioconductor tools and statistical techniques to account for the large heterogeneity and sparsity found in very large RNA-seq experiments.") (license license:artistic2.0))) (define-public r-roar (package (name "r-roar") (version "1.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "roar" version)) (sha256 (base32 "0p5q6nyp8d0gl95rd89xrs08gv87m1q6d0x4ws2b6sd4gc1nw2ny")))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-genomeinfodb r-genomicalignments r-genomicranges r-iranges r-rtracklayer r-s4vectors r-summarizedexperiment)) (home-page "https://github.com/vodkatad/roar/") (synopsis "Identify differential APA usage from RNA-seq alignments") (description "This package provides tools for identifying preferential usage of APA sites, comparing two biological conditions, starting from known alternative sites and alignments obtained from standard RNA-seq experiments.") (license license:gpl3))) (define-public r-xbseq (package (name "r-xbseq") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "XBSeq" version)) (sha256 (base32 "1dvk2jpsdynqw5071z54yd5j0ddprhc1ppk834cz9liibd72d7vz")))) (properties `((upstream-name . "XBSeq"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-deseq2 r-dplyr r-ggplot2 r-locfit r-magrittr r-matrixstats r-pracma r-roar)) (native-inputs (list r-knitr)) (home-page "https://github.com/Liuy12/XBSeq") (synopsis "Test for differential expression for RNA-seq data") (description "XBSeq is a novel algorithm for testing RNA-seq @dfn{differential expression} (DE), where a statistical model was established based on the assumption that observed signals are the convolution of true expression signals and sequencing noises. The mapped reads in non-exonic regions are considered as sequencing noises, which follows a Poisson distribution. 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(license license:gpl2+))) (define-public r-wppi (package (name "r-wppi") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "wppi" version)) (sha256 (base32 "06y4pq8msjzwrw1jgyj9yskgpfhvcz54qcsv0h14bakhyrwk00pg")))) (properties `((upstream-name . "wppi"))) (build-system r-build-system) ;; This is necessary because omnipathr attempts to write a configuration ;; file to HOME. (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 "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Wrench" version)) (sha256 (base32 "18x12395928d0mf8kffmdjqkdxrzgqzzhhvs7sdzldwyas6hfg2h")))) (properties `((upstream-name . 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The model also accounts for the difference in library sizes and optionally for batch effects and/or other covariates, avoiding the need for pre-normalize the data.") (license license:artistic2.0))) (define-public r-zfpkm (package (name "r-zfpkm") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "zFPKM" version)) (sha256 (base32 "1fkzyq282xafyapgi5xi1c2dmfkyikqvf622pycjs80fas38044h")))) (properties `((upstream-name . "zFPKM"))) (build-system r-build-system) (propagated-inputs (list r-checkmate r-dplyr r-ggplot2 r-summarizedexperiment r-tidyr)) (native-inputs (list r-knitr)) (home-page "https://github.com/ronammar/zFPKM/") (synopsis "Functions to facilitate zFPKM transformations") (description "This is a package to perform the zFPKM transform on RNA-seq FPKM data. This algorithm is based on the publication by Hart et al., 2013 (Pubmed ID 24215113).") 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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 "1.40.1") (source (origin (method url-fetch) (uri (bioconductor-uri "QuasR" version)) (sha256 (base32 "08vns1wbgpxw1x6djp84f9hl3gqaybbw9917ghfzk0x3ijpvggbg")))) (properties `((upstream-name . "QuasR"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-biobase r-biocgenerics r-biocparallel r-biostrings r-bsgenome r-genomeinfodb r-genomicfeatures r-genomicfiles r-genomicranges r-iranges r-rbowtie r-rhtslib r-rsamtools r-rtracklayer r-s4vectors r-shortread)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/QuasR/") (synopsis "Quantify and annotate short reads in R") (description "This package provides a framework for the quantification and analysis of short genomic reads. 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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 "3.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "BiRewire" version)) (sha256 (base32 "1741raw1834093y5zhgx9jywfgz0wl0idlkynvab2c8vi40kc9a8")))) (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 "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MultiDataSet" version)) (sha256 (base32 "1qyvwhmdv27xsyljyzyh52pn6x0wqx8rslvr2j7vqcjyywv270x6")))) (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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(license license:expat))) (define-public r-ropls (package (name "r-ropls") (version "1.32.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ropls" version)) (sha256 (base32 "1cq5ixaxag5r6nvl73c8bznxkdjhxw1r7qx90ml7qm4jr7wyi173")))) (build-system r-build-system) (propagated-inputs (list r-biobase r-ggplot2 r-multiassayexperiment r-multidataset r-plotly r-summarizedexperiment)) (native-inputs (list r-knitr)) ; for vignettes (home-page "https://dx.doi.org/10.1021/acs.jproteome.5b00354") (synopsis "Multivariate analysis and feature selection of omics data") (description "Latent variable modeling with @dfn{Principal Component Analysis} (PCA) and @dfn{Partial Least Squares} (PLS) are powerful methods for visualization, regression, classification, and feature selection of omics data where the number of variables exceeds the number of samples and with multicollinearity among variables. @dfn{Orthogonal Partial Least Squares} (OPLS) enables to separately model the variation correlated (predictive) to the factor of interest and the uncorrelated (orthogonal) variation. While performing similarly to PLS, OPLS facilitates interpretation. This package provides imlementations of PCA, PLS, and OPLS for multivariate analysis and feature selection of omics data. In addition to scores, loadings and weights plots, the package provides metrics and graphics to determine the optimal number of components (e.g. with the R2 and Q2 coefficients), check the validity of the model by permutation testing, detect outliers, and perform feature selection (e.g. with Variable Importance in Projection or regression coefficients).") 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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 "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "annotatr" version)) (sha256 (base32 "1vjbk1vpqjxy9wv2a6sc32yyk0bhkbvdx9hl3vs5yjifwdswh2pw")))) (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. 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"ggcyto"))) (build-system r-build-system) (propagated-inputs (list r-data-table r-flowcore r-flowworkspace r-ggplot2 r-gridextra r-hexbin r-ncdfflow r-plyr r-rcolorbrewer r-rlang r-scales)) (native-inputs (list r-knitr)) (home-page "https://github.com/RGLab/ggcyto/issues") (synopsis "Visualize Cytometry data with ggplot") (description "With the dedicated fortify method implemented for @code{flowSet}, @code{ncdfFlowSet} and @code{GatingSet} classes, both raw and gated flow cytometry data can be plotted directly with ggplot. The @code{ggcyto} wrapper and some custom layers also make it easy to add gates and population statistics to the plot.") (license license:artistic2.0))) (define-public r-flowviz (package (name "r-flowviz") (version "1.64.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowViz" version)) (sha256 (base32 "0y16hzadpr5c99cwkphc07vh6lypgfk5nacbmn7mmrw01b3gbk67")))) (properties `((upstream-name . 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"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 "4.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowStats" version)) (sha256 (base32 "13mdpdndalm0d6azjancw0xcbdc674ivkj8kp6ccfpdd7gydhr4j")))) (properties `((upstream-name . "flowStats"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics 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 "2.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "openCyto" version)) (sha256 (base32 "0z0p09mkap1jqlq1x33i2ik87pbhwq85xgqyfsx4r360nhv06pna")))) (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 "2.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "CytoML" version)) (sha256 (base32 "19rlg15nk2205vma4whpqmvlazww5i3ibxhmk9cljsaj4ql560vf")))) (properties `((upstream-name . "CytoML"))) (build-system r-build-system) (inputs (list libxml2 #;zlib )) (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 "2.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "FlowSOM" version)) (sha256 (base32 "13y0ny61skj14mfhjwpa5zmflzdqxy2vf6gd4m9358g4wxfbhkv0")))) (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 "6.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mixOmics" version)) (sha256 (base32 "0dqndpmi56g772sra49vdrkjs4m9h2gzimwv3bwmw2l0krh2ax8s")))) (properties `((upstream-name . "mixOmics"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-corpcor r-dplyr r-ellipse r-ggrepel r-ggplot2 r-gridextra r-igraph r-lattice r-mass r-matrixstats r-rarpack r-rcolorbrewer r-reshape2 r-tidyr)) (native-inputs (list r-knitr)) (home-page "http://www.mixOmics.org") (synopsis "Multivariate methods for exploration of biological datasets") (description "mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data.") (license license:gpl2+))) (define-public r-depecher (package ;Source/Weave error (name "r-depecher") (version "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DepecheR" version)) (sha256 (base32 "1kn1w1fs19gjvg8nhbvj6hyp32h6k81dnal4ab12xl1jgaa3xj5p")))) (properties `((upstream-name . 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(license license:expat))) (define-public r-rcistarget (package (name "r-rcistarget") (version "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "RcisTarget" version)) (sha256 (base32 "0dp2y85mfn995rvg698xnxlkz1kd8g0byjypxx62cpfldnkrinxl")))) (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)) (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 "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Chicago" version)) (sha256 (base32 "04h4a5nyc78jlsg9pj8ay559bwb8y1nm80v9zvyxd7r490yn7k7s")))) (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 "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "cicero" version)) (sha256 (base32 "12zdygnwqjla99wzvvxzcmiwmh4v0rmnx4yix02gbj8xl4bxmm51")))) (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 "1.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "circRNAprofiler" version)) (sha256 (base32 "0gagfm7v5bnnfj1zy6zf4cg91bj8nvv4vm38f3a1s4q2xc8pcvfj")))) (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 . 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(license license:gpl2+))) (define-public r-roc (package (name "r-roc") (version "1.76.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ROC" version)) (sha256 (base32 "0fq59bwc5i8zdw0v0jr5j5lm4hk6p7b88i2xndsgj4fq65yr50g1")))) (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 "2.6.0") (source (origin (method url-fetch) (uri (bioconductor-uri "wateRmelon" version)) (sha256 (base32 "0qslh2xhhyaf0nsgcqav6qgh05n8kp0s6p1zggc02iid30i1ibrj")))) (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 "1.36.1") (source (origin (method url-fetch) (uri (bioconductor-uri "gdsfmt" version)) (sha256 (base32 "11qib2znznzvyb0x9qm1nfg9lhyqy63yrdjicy7n3n6l8dfd2lx7")) (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 . 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(license license:gpl2))) (define-public r-omnipathr (package (name "r-omnipathr") (version "3.8.2") (source (origin (method url-fetch) (uri (bioconductor-uri "OmnipathR" version)) (sha256 (base32 "13ac98jj03vkzrc1ghrs98qrfvr74wz099w26lgc7jw2yxj575as")))) (properties `((upstream-name . "OmnipathR"))) (build-system r-build-system) (arguments `(#:phases (modify-phases %standard-phases (add-after 'unpack 'set-HOME (lambda _ (setenv "HOME" "/tmp")))))) (propagated-inputs (list r-checkmate r-crayon r-curl r-digest r-dplyr r-httr r-igraph r-jsonlite r-later r-logger r-magrittr r-progress r-purrr r-rappdirs r-readr r-readxl r-rlang r-rmarkdown r-rvest r-stringr r-tibble r-tidyr r-tidyselect r-withr r-xml2 r-yaml)) (native-inputs (list r-knitr)) (home-page "https://saezlab.github.io/OmnipathR/") (synopsis "OmniPath web service client and more") (description "This package provides a client for the OmniPath web service and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data.") (license license:expat))) (define-public r-biscuiteer (package (name "r-biscuiteer") (version "1.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "biscuiteer" version)) (sha256 (base32 "07nak6mfw9m8ldl336sqgkl3638ibv1hxwd89hwxdrn914wz3hw3")))) (properties `((upstream-name . "biscuiteer"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-biocgenerics r-biocparallel r-biscuiteerdata r-bsseq r-data-table r-delayedmatrixstats r-dmrseq r-genomeinfodb r-genomicranges r-gtools r-hdf5array r-homo-sapiens r-impute r-iranges r-matrix r-matrixstats r-mus-musculus r-qdnaseq r-qualv r-r-utils r-readr r-rsamtools r-rtracklayer r-s4vectors r-summarizedexperiment r-variantannotation)) (native-inputs (list r-knitr)) (home-page "https://github.com/trichelab/biscuiteer") (synopsis "Convenience functions for the Biscuit package") (description "This package provides a test harness for bsseq loading of Biscuit output, summarization of WGBS data over defined regions and in mappable samples, with or without imputation, dropping of mostly-NA rows, age estimates, etc.") (license license:gpl3))) (define-public r-tcgabiolinks (package (name "r-tcgabiolinks") (version "2.28.3") (source (origin (method url-fetch) (uri (bioconductor-uri "TCGAbiolinks" version)) (sha256 (base32 "1hh09ya4jg062k1ibp1cpvdrgv6gwr95ch57iycgd3cjc5g0xhii")))) (properties `((upstream-name . "TCGAbiolinks"))) (build-system r-build-system) (propagated-inputs (list r-biomart r-data-table r-downloader r-dplyr r-genomicranges r-ggplot2 r-httr r-iranges r-jsonlite r-knitr r-plyr r-purrr r-r-utils r-readr r-rvest r-s4vectors r-stringr r-summarizedexperiment r-tcgabiolinksgui-data r-tibble r-tidyr r-xml r-xml2)) (native-inputs (list r-knitr)) (home-page "https://github.com/BioinformaticsFMRP/TCGAbiolinks") (synopsis "Integrative analysis with GDC data") (description "The aim of TCGAbiolinks is: @enumerate @item facilitate GDC open-access data retrieval; @item prepare the data using the appropriate pre-processing strategies; @item provide the means to carry out different standard analyses, and; @item to easily reproduce earlier research results. @end enumerate In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.") (license license:gpl3+))) (define-public r-tricycle (package (name "r-tricycle") (version "1.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tricycle" version)) (sha256 (base32 "1ags05rhi431jsk0kqs7rmxj853mf5c0ibfqknbwy2wmbz8p1vq6")))) (properties `((upstream-name . "tricycle"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-circular r-dplyr r-genomicranges r-ggnewscale r-ggplot2 r-iranges r-rcolorbrewer r-s4vectors r-scater r-scattermore r-singlecellexperiment r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://github.com/hansenlab/tricycle") (synopsis "Transferable representation and inference of cell cycle") (description "The package contains functions to infer and visualize cell cycle process using Single-cell RNA-Seq data. It exploits the idea of transfer learning, projecting new data to the previous learned biologically interpretable space. The @code{tricycle} provides a pre-learned cell cycle space, which could be used to infer cell cycle time of human and mouse single cell samples. In addition, it also offer functions to visualize cell cycle time on different embeddings and functions to build new reference.") (license license:gpl3))) (define-public r-tximeta (package (name "r-tximeta") (version "1.18.3") (source (origin (method url-fetch) (uri (bioconductor-uri "tximeta" version)) (sha256 (base32 "01s8x8a3rb0a5i599pxc5miz84ssvh10b4vha79nmbhkqccffvml")))) (properties `((upstream-name . "tximeta"))) (build-system r-build-system) (propagated-inputs (list r-annotationdbi r-annotationhub r-biocfilecache r-biostrings r-ensembldb r-genomeinfodb r-genomicfeatures r-genomicranges r-iranges r-jsonlite r-matrix r-s4vectors r-summarizedexperiment r-tibble r-tximport)) (native-inputs (list r-knitr)) (home-page "https://github.com/mikelove/tximeta") (synopsis "Transcript quantification import with automatic metadata") (description "This package implements transcript quantification import from Salmon and alevin with automatic attachment of transcript ranges and release information, and other associated metadata. De novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for computational reproducibility.") (license license:gpl2))) (define-public r-phyloseq (package (name "r-phyloseq") (version "1.44.0") (source (origin (method url-fetch) (uri (bioconductor-uri "phyloseq" version)) (sha256 (base32 "0rmv8f1m8ck97v991wdly3fma2rjczhi974lh7ikwx6rcx6fp9ah")))) (properties `((upstream-name . "phyloseq"))) (build-system r-build-system) (propagated-inputs (list r-ade4 r-ape r-biobase r-biocgenerics r-biomformat r-biostrings r-cluster r-data-table r-foreach r-ggplot2 r-igraph r-multtest r-plyr r-reshape2 r-scales r-vegan)) (native-inputs (list r-knitr)) (home-page "https://github.com/joey711/phyloseq") (synopsis "Handling and analysis of high-throughput microbiome census data") (description "Phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.") (license license:agpl3))) ;;; ;;; Avoid adding new packages to the end of this file. To reduce the chances ;;; of a merge conflict, place them above by existing packages with similar ;;; functionality or similar names. ;;;