;;; 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 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 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-mousegastrulationdata (package (name "r-mousegastrulationdata") (version "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MouseGastrulationData" version 'experiment)) (sha256 (base32 "0m03wrqgfhlyc0rmjjcj8b9gcc2rv644hffnff3j1bnkjg5rldi0")))) (properties `((upstream-name . "MouseGastrulationData"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-bumpymatrix r-experimenthub r-s4vectors r-singlecellexperiment r-spatialexperiment r-summarizedexperiment)) (native-inputs (list r-knitr)) (home-page "https://github.com/MarioniLab/MouseGastrulationData") (synopsis "Single-Cell omics data across mouse gastrulation and early organogenesis") (description "This package provides processed and raw count data for single-cell RNA sequencing. 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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 "1.44.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ALL" version 'experiment)) (sha256 (base32 "1ny5xv338a91gc88a1y5rrd27iawrrlmxhkidvc7xdsbrwd4flkc")))) (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 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 "1.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "derfinder" version)) (sha256 (base32 "0rj3szlpbxiwj3rajmr6ccnbs1mkcskql12iip8zgswmhz76rxh1")))) (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 "1.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DRIMSeq" version)) (sha256 (base32 "1nf044cfqywfnglm081xbppamva87z2j2xz0f51z8mra11apj6i6")))) (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 "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DropletUtils" version)) (sha256 (base32 "0bnxk72a0ygh4nqwyjzzi79zc4md8pwk0pr6jn43in0wdk054wf6")))) (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 "2.50.1") (source (origin (method url-fetch) (uri (bioconductor-uri "DSS" version)) (sha256 (base32 "1wjd428kz2w3n4ak13h3i1yknm03fh911jrcy2hkcip4z5cssla0")))) (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 "1.80.0") (source (origin (method url-fetch) (uri (bioconductor-uri "DynDoc" version)) (sha256 (base32 "0d2axaszy7rpi47yg4vhd1z70m53nx40znapgg5pq6ahrx7if5f1")))) (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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A heatmap is generated illustrating the relative expression intensities across each chromosome, and it often becomes readily apparent as to which regions of the tumor genome are over-abundant or less-abundant as compared to that of normal cells.") (license license:bsd-3))) (define-public r-iranges (package (name "r-iranges") (version "2.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "IRanges" version)) (sha256 (base32 "0rhh82hrsm32bdjamfah84p7zi8fvr4shyq2rdjfxzdp9qy5rh2q")))) (properties `((upstream-name . 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(define-public r-isva (package (name "r-isva") (version "1.9") (source (origin (method url-fetch) (uri (cran-uri "isva" version)) (sha256 (base32 "05qx9q0kg4ma23v4abhihw0vz017nq6hv2jzsiqx4d20ngh1dl4z")))) (properties `((upstream-name . "isva"))) (build-system r-build-system) (propagated-inputs (list r-fastica r-jade r-qvalue)) (home-page "https://cran.r-project.org/package=isva") (synopsis "Independent surrogate variable analysis") (description "Independent Surrogate Variable Analysis is an algorithm for feature selection in the presence of potential confounding factors (see Teschendorff AE et al 2011, ).") (license license:gpl2))) (define-public r-italics (package (name "r-italics") (version "2.62.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ITALICS" version)) (sha256 (base32 "0zk9n94nqw6vpw908ka32zppxwqkki9krzxib06y1nic3bri3w9i")))) (properties `((upstream-name . 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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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This can present a mild conundrum when attempting to evaluate a gene \"signature\" that is defined by gene names rather than by specific probe sets. This package also includes the pre-calculated probe set quality scores that were used to define the mapping.") (license license:artistic2.0))) (define-public r-nebulosa (package (name "r-nebulosa") (version "1.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Nebulosa" version)) (sha256 (base32 "0kzkdwxrhl7plbcbqr58gnadhhbhx2811ian0s4kds14y4mxl26c")))) (properties `((upstream-name . 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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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This package is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.") (license license:artistic2.0))) (define-public r-metaneighbor (package (name "r-metaneighbor") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MetaNeighbor" version)) (sha256 (base32 "0y8nk9jq0z48phg13mf6hsfg8l54w6z6b67g0k1c9gmsb7aqq04d")))) (properties `((upstream-name . 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In depth exploration of bad quality samples can be performed using several interactive diagnostic plots of the quality control probes present on the array. Furthermore, the impact of any batch effect provided by the user can be explored.") (license license:gpl2+))) (define-public r-methylkit (package (name "r-methylkit") (version "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "methylKit" version)) (sha256 (base32 "0y45wa45kblm2g3nylvybvyfc34sjlynhsz3dirhs1favb83sdiv")))) (properties `((upstream-name . 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(license license:artistic2.0))) (define-public r-mfuzz (package (name "r-mfuzz") (version "2.62.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Mfuzz" version)) (sha256 (base32 "0v2l3fi9331lxfam6az265rfk52g4n75hh4rg12ykhp86ihplzpf")))) (properties `((upstream-name . "Mfuzz"))) (build-system r-build-system) (propagated-inputs (list r-biobase r-e1071 r-tkwidgets)) (home-page "http://mfuzz.sysbiolab.eu/") (synopsis "Soft clustering of time series gene expression data") (description "This is a package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface).") (license license:gpl2))) (define-public r-mmuphin (package (name "r-mmuphin") (version "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MMUPHin" version)) (sha256 (base32 "0lhvsx5yjvqh5d3h860sv8cf3h73nrzvljpkqrd9ks0irc4gcm6d")) ;; Delete generated files. (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 "1.18.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Modstrings" version)) (sha256 (base32 "1jjawwkvdx02ss2vw4ah2b8psgxr01z6r1rkr2pnkmrp2ma7ygks")))) (properties `((upstream-name . 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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.") 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(license license:gpl3))) (define-public r-mutationalpatterns (package (name "r-mutationalpatterns") (version "3.12.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MutationalPatterns" version)) (sha256 (base32 "19ya4ax6pa727hdn0118l9pwa9dxgh89dz54mm66dawxga3jhar4")))) (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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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 "1.40.0") (source (origin (method url-fetch) (uri (bioconductor-uri "mzID" version)) (sha256 (base32 "1rgkd9iv0lxj1zxh96sifwa312ivw5kl5jw82ma4fmapr4iqhzsh")))) (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.") 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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 . 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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 "1.30.1") (source (origin (method url-fetch) (uri (bioconductor-uri "Organism.dplyr" version)) (sha256 (base32 "1s55fiqgxrdznn43qhm5yv9gp8d1msr2f39wxih0b5bm4wxhkq45")))) (properties `((upstream-name . 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(define-public r-pscbs (package (name "r-pscbs") (version "0.66.0") (source (origin (method url-fetch) (uri (cran-uri "PSCBS" version)) (sha256 (base32 "14rs2wywipbkia3dbzfhpnkmfgdvm2bf586lggsx63sywlv5d02q")))) (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. 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The result is a single output depicting the variation across all conditions. @code{XINA} not only extracts coabundance profiles within and across experiments, but also incorporates protein-protein interaction databases and integrative resources such as @dfn{Kyoto encyclopedia of genes and genomes} (KEGG) to infer interactors and molecular functions, respectively, and produces intuitive graphical outputs.") (license license:gpl3))) (define-public r-xmapbridge (package (name "r-xmapbridge") (version "1.60.0") (source (origin (method url-fetch) (uri (bioconductor-uri "xmapbridge" version)) (sha256 (base32 "0pby2h8m12xlngpk33dvh3nkrpgqi4f2mb7g9jafyiv3sl8pjd19")))) (properties `((upstream-name . "xmapbridge"))) (build-system r-build-system) (home-page "https://git.bioconductor.org/packages/xmapbridge") (synopsis "Display numeric data in the web based genome browser X:MAP") (description "The package @code{xmapbridge} can plot graphs in the X:Map genome browser. 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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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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.") 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An \"intelligent\" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.") (license license:gpl2))) (define-public r-lefser (package (name "r-lefser") (version "1.12.1") (source (origin (method url-fetch) (uri (bioconductor-uri "lefser" version)) (sha256 (base32 "0aywwinp4wwwa12rq60gpfk5gn28zyimayxakgj4lhfwjk0byz8m")))) (properties `((upstream-name . 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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 "2.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "IONiseR" version)) (sha256 (base32 "1y595hq40kpsasp74wsbf3ngd2rrriqg65z9y4svcwdygj03pgrz")))) (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.") 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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 "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "anota2seq" version)) (sha256 (base32 "0kyxwhj5vq5z4v3x3hfb9ks3h37axqskyj9rzyj2bzsy2yk9hajn")))) (properties `((upstream-name . 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(define-public r-cytolib (package (name "r-cytolib") (version "2.14.1") (source (origin (method url-fetch) (uri (bioconductor-uri "cytolib" version)) (sha256 (base32 "1kagik93ddcl3m1i2bqzzlh18lbxywfn3pxmp47p45kayzxzldrf")))) (properties `((upstream-name . "cytolib"))) (build-system r-build-system) (inputs (list openblas protobuf zlib)) (native-inputs (list r-knitr)) (propagated-inputs (list r-bh r-rhdf5lib r-rprotobuflib)) (home-page "https://bioconductor.org/packages/cytolib/") (synopsis "C++ infrastructure for working with gated cytometry") (description "This package provides the core data structure and API to represent and interact with gated cytometry data.") (license license:artistic2.0))) (define-public r-flowcore (package (name "r-flowcore") (version "2.14.0") (source (origin (method url-fetch) (uri (bioconductor-uri "flowCore" version)) (sha256 (base32 "11aic1nzlw0gdpcpmky5jzljxgxcrimi29f0zl3yjvgb48qa88bd")))) (properties `((upstream-name . 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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 "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "RcisTarget" version)) (sha256 (base32 "0dp2y85mfn995rvg698xnxlkz1kd8g0byjypxx62cpfldnkrinxl")))) (properties `((upstream-name . 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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 "1.30.0") (source (origin (method url-fetch) (uri (bioconductor-uri "Chicago" version)) (sha256 (base32 "1mcpx785ag0jcsh08df34hx3wp55zd1vggnl3fflkinb78178n38")))) (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 "1.20.0") (source (origin (method url-fetch) (uri (bioconductor-uri "cicero" version)) (sha256 (base32 "19vn31w74r45pq5m9pn5db1sz1qg757mghzzs933cdssnqf4m6y5")))) (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 "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "circRNAprofiler" version)) (sha256 (base32 "098fbrszph5cnh4n9zjhj92sg1bi6h6k57wm2vlaqkq0nab63r63")))) (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 "1.24.0") (source (origin (method url-fetch) (uri (bioconductor-uri "GENIE3" version)) (sha256 (base32 "0bsid8qhcqgalqghr2b2592pzm4viyi7wq8h5dmhrrl7gky8l60k")))) (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 "1.78.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ROC" version)) (sha256 (base32 "12msc6skvcx4ajk20l71k32rj8lsiafjxwcsrd51kyy5x2yj2v4m")))) (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 "2.8.0") (source (origin (method url-fetch) (uri (bioconductor-uri "wateRmelon" version)) (sha256 (base32 "1ra21qzni9cny52ag9zxi46vb9grabyqjyk01dqqp3r9i0b4999l")))) (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 "1.38.0") (source (origin (method url-fetch) (uri (bioconductor-uri "gdsfmt" version)) (sha256 (base32 "03qgiww523kijrkciln3fw3djn20rnvwz2j0i3p518h6fbl7vlpm")) (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 "1.28.0") (source (origin (method url-fetch) (uri (bioconductor-uri "bigmelon" version)) (sha256 (base32 "1j80f7k39p23s6fym3nia73g8d1v44hdiv73igcq6fnsllxg40hr")))) (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.") (license license:lgpl3))) (define-public r-reqon (package (name "r-reqon") (version "1.48.0") (source (origin (method url-fetch) (uri (bioconductor-uri "ReQON" version)) (sha256 (base32 "0w28b3ma8r8rshijdm5jj1z64v91my7hcvw18r9pdwjprh05bw0g")))) (properties `((upstream-name . "ReQON"))) (build-system r-build-system) (propagated-inputs (list r-rjava r-rsamtools r-seqbias)) (home-page "https://bioconductor.org/packages/ReQON/") (synopsis "Recalibrating quality of nucleotides") (description "This package provides an implementation of an algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format.") (license license:gpl2))) (define-public r-wavcluster (package (name "r-wavcluster") (version "2.36.0") (source (origin (method url-fetch) (uri (bioconductor-uri "wavClusteR" version)) (sha256 (base32 "1y2bk1kla0l72xgdam2l9c0k7584ckdqscqnc184cxvqm6fb335j")))) (properties `((upstream-name . "wavClusteR"))) (build-system r-build-system) (propagated-inputs (list r-biocgenerics r-biostrings r-foreach r-genomicfeatures r-genomicranges r-ggplot2 r-hmisc r-iranges r-mclust r-rsamtools r-rtracklayer r-s4vectors r-seqinr r-stringr)) (native-inputs (list r-knitr)) (home-page "https://bioconductor.org/packages/wavClusteR/") (synopsis "Identification of RNA-protein interaction sites in PAR-CLIP data") (description "This package provides an integrated pipeline for the analysis of PAR-CLIP data. PAR-CLIP-induced transitions are first discriminated from sequencing errors, SNPs and additional non-experimental sources by a non- parametric mixture model. The protein binding sites (clusters) are then resolved at high resolution and cluster statistics are estimated using a rigorous Bayesian framework. Post-processing of the results, data export for UCSC genome browser visualization and motif search analysis are provided. 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 "1.80.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tilingArray" version)) (sha256 (base32 "01j4wj0mdfrlyhp2alf1xfy78f17x43w9i0wb41ljw6pm313np58")))) (properties `((upstream-name . "tilingArray"))) (build-system r-build-system) (propagated-inputs (list r-affy r-biobase r-genefilter r-pixmap r-rcolorbrewer r-strucchange r-vsn)) (home-page "https://bioconductor.org/packages/tilingArray") (synopsis "Transcript mapping with high-density oligonucleotide tiling arrays") (description "The package provides functionality that can be useful for the analysis of the high-density tiling microarray data (such as from Affymetrix genechips) or for measuring the transcript abundance and the architecture. The main functionalities of the package are: @enumerate @item the class segmentation for representing partitionings of a linear series of data; @item the function segment for fitting piecewise constant models using a dynamic programming algorithm that is both fast and exact; @item the function @code{confint} for calculating confidence intervals using the @code{strucchange} package; @item the function @code{plotAlongChrom} for generating pretty plots; @item the function @code{normalizeByReference} for probe-sequence dependent response adjustment from a (set of) reference hybridizations. @end enumerate") (license license:artistic2.0))) (define-public r-timeseriesexperiment (package (name "r-timeseriesexperiment") (version "1.13.0") (source (origin (method url-fetch) (uri (bioconductor-uri "TimeSeriesExperiment" version)) (sha256 (base32 "0bdpxxr739qdg92qabfx122k9f43vw2hyxp4yxqlbp37vzgcdf2c")))) (properties `((upstream-name . 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(license license:gpl2+))) (define-public r-htqpcr (package (name "r-htqpcr") (version "1.56.0") (source (origin (method url-fetch) (uri (bioconductor-uri "HTqPCR" version)) (sha256 (base32 "14cff36ikbqhd5xizihpxzsv9jimcpbgnd381jd154pgi60bil0m")))) (properties `((upstream-name . "HTqPCR"))) (build-system r-build-system) (propagated-inputs (list r-affy r-biobase r-gplots r-limma r-rcolorbrewer)) (home-page (string-append "https://www.ebi.ac.uk/sites/ebi.ac.uk/files/" "groups/bertone/software/HTqPCR.pdf")) (synopsis "Automated analysis of high-throughput qPCR data") (description "Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. 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The design of this API is intended to match the Python API and other tools included with the biom-format project, but with a decidedly \"R flavor\" that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.") (license license:gpl2))) (define-public r-mvcclass (package (name "r-mvcclass") (version "1.76.0") (source (origin (method url-fetch) (uri (bioconductor-uri "MVCClass" version)) (sha256 (base32 "16finp6q89n6x5q2v1khpfp5ys7d4dvlh3kacv5qbdh1bsb3fpax")))) (properties `((upstream-name . "MVCClass"))) (build-system r-build-system) (home-page "https://bioconductor.org/packages/MVCClass") (synopsis "Model-View-Controller (MVC) classes") (description "This package contains classes used in model-view-controller (MVC) design.") 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(license license:gpl2+))) (define-public r-bionero (package (name "r-bionero") (version "1.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "BioNERO" version)) (sha256 (base32 "0pq5fiacb2x8l5jk3p6bnha9bcwg91grpklgx2nirrlwwr80gf2h")))) (properties `((upstream-name . "BioNERO"))) (build-system r-build-system) (propagated-inputs (list r-biocparallel r-complexheatmap r-dynamictreecut r-genie3 r-ggdendro r-ggnetwork r-ggplot2 r-ggrepel r-igraph r-intergraph r-matrixstats r-minet r-netrep r-patchwork r-rcolorbrewer r-reshape2 r-rlang r-summarizedexperiment r-sva r-wgcna)) (native-inputs (list r-knitr)) (home-page "https://github.com/almeidasilvaf/BioNERO") (synopsis "Biological network reconstruction omnibus") (description "BioNERO aims to integrate all aspects of biological network inference in a single package, including data preprocessing, exploratory analyses, network inference, and analyses for biological interpretations. BioNERO can be used to infer gene coexpression networks (GCNs) and gene regulatory networks (GRNs) from gene expression data. Additionally, it can be used to explore topological properties of protein-protein interaction (PPI) networks. GCN inference relies on the popular WGCNA algorithm. GRN inference is based on the \"wisdom of the crowds\" principle, which consists in inferring GRNs with multiple algorithms (here, CLR, GENIE3 and ARACNE) and calculating the average rank for each interaction pair. As all steps of network analyses are included in this package, BioNERO makes users avoid having to learn the syntaxes of several packages and how to communicate between them. Finally, users can also identify consensus modules across independent expression sets and calculate intra and interspecies module preservation statistics between different networks.") 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By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.") (license license:gpl2+))) (define-public r-bionetstat (package (name "r-bionetstat") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "BioNetStat" version)) (sha256 (base32 "1rbb36v64b9xbk2dsf6wsyrhwwbkysrj8fp1g22y3gisdk170sg8")) (snippet '(delete-file "inst/datatables/js/jquery.dataTables.min.js")))) (properties `((upstream-name . 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(license license:gpl3+))) (define-public r-biotip (package (name "r-biotip") (version "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "BioTIP" version)) (sha256 (base32 "1bbjfv3bi20xlk8h7r5ipav6mfs27lmj0zjb5mk1gmp071dmnk0y")))) (properties `((upstream-name . "BioTIP"))) (build-system r-build-system) (propagated-inputs (list r-cluster r-genomicranges r-igraph r-mass r-psych r-scran r-stringr)) (native-inputs (list r-knitr)) (home-page "https://github.com/xyang2uchicago/BioTIP") (synopsis "R package for characterization of biological tipping-point") (description "This package adopts tipping-point theory to transcriptome profiles to help unravel disease regulatory trajectory.") (license license:gpl2))) (define-public r-biotmle (package (name "r-biotmle") (version "1.26.0") (source (origin (method url-fetch) (uri (bioconductor-uri "biotmle" version)) (sha256 (base32 "0h796sxv7fvwx9m8ikamf3bvaac7rimp33lv1j3ngsjifigdkvfy")))) (properties `((upstream-name . 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Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.") (license license:lgpl2.0))) (define-public r-dmrseq (package (name "r-dmrseq") (version "1.22.0") (source (origin (method url-fetch) (uri (bioconductor-uri "dmrseq" version)) (sha256 (base32 "0z53vh5qirkyn7yw3g2m2kj6dzii96l81vc8j59n2dl7p602l9a2")))) (properties `((upstream-name . 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Region-level statistics are obtained by fitting a @dfn{generalized least squares} (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.") (license license:expat))) (define-public r-omicade4 (package (name "r-omicade4") (version "1.42.0") (source (origin (method url-fetch) (uri (bioconductor-uri "omicade4" version)) (sha256 (base32 "0i4ln95ayl1irr8sr3639x35ilysdi663kksw7g93q1ry91yav8r")))) (properties `((upstream-name . "omicade4"))) (build-system r-build-system) (propagated-inputs (list r-ade4 r-biobase r-made4)) (home-page "https://bioconductor.org/packages/omicade4") (synopsis "Multiple co-inertia analysis of omics datasets") (description "This package performes multiple co-inertia analysis of omics datasets.") (license license:gpl2))) (define-public r-omnipathr (package (name "r-omnipathr") (version "3.10.1") (source (origin (method url-fetch) (uri (bioconductor-uri "OmnipathR" version)) (sha256 (base32 "1wbzb4kh7bzsvixr3vxzih9rfkpjx00f33i0yl0dqj0yixnrghwr")))) (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-lubridate r-magrittr r-progress r-purrr r-rappdirs r-readr r-readxl r-rlang r-rmarkdown r-rvest r-stringi 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 "1.16.0") (source (origin (method url-fetch) (uri (bioconductor-uri "biscuiteer" version)) (sha256 (base32 "1q90p14qj5plz6cbvwxq875y29in6jg7adyni5wd33pf9i4gsxzi")))) (properties `((upstream-name . 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(license license:gpl3+))) (define-public r-tricycle (package (name "r-tricycle") (version "1.10.0") (source (origin (method url-fetch) (uri (bioconductor-uri "tricycle" version)) (sha256 (base32 "1dawkp681pz9hf7fp2nag9pcfxx5rq0z4j9czlalf0sylsjbirkd")))) (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. 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(license license:gpl2))) (define-public r-phyloseq (package (name "r-phyloseq") (version "1.46.0") (source (origin (method url-fetch) (uri (bioconductor-uri "phyloseq" version)) (sha256 (base32 "06gnpjcniqm8i52xh9xl3nn0wm9nn9rkqd3w3fjv7ii142xypjln")))) (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. ;;;