tumor samples from healthy controls.")
(license license:artistic2.0)))
+(define-public r-assessorf
+ (package
+ (name "r-assessorf")
+ (version "1.14.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "AssessORF" version))
+ (sha256
+ (base32
+ "1l87bpny9k3jbzbzmb9h2ijvblrj471gqv26fyzbvb3vr6y406z7"))))
+ (properties `((upstream-name . "AssessORF")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-biostrings
+ r-decipher
+ r-genomicranges
+ r-iranges))
+ (native-inputs (list r-knitr))
+ (home-page "https://bioconductor.org/packages/AssessORF")
+ (synopsis "Assess gene predictions using proteomics and evolutionary conservation")
+ (description
+ "In order to assess the quality of a set of predicted genes for a genome,
+evidence must first be mapped to that genome. Next, each gene must be
+categorized based on how strong the evidence is for or against that gene. The
+AssessORF package provides the functions and class structures necessary for
+accomplishing those tasks, using proteomics hits and evolutionarily conserved
+start codons as the forms of evidence.")
+ (license license:gpl3)))
+
+(define-public r-asset
+ (package
+ (name "r-asset")
+ (version "2.14.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "ASSET" version))
+ (sha256
+ (base32
+ "029acl5k9d4hnvy3jia9cr4rk6w31zn8b5s79i6lazq1cp236hbg"))))
+ (properties `((upstream-name . "ASSET")))
+ (build-system r-build-system)
+ (propagated-inputs (list r-mass r-msm r-rmeta))
+ (native-inputs (list r-knitr))
+ (home-page "https://bioconductor.org/packages/ASSET")
+ (synopsis
+ "Subset-based association analysis of heterogeneous traits and subtypes")
+ (description
+ "This package is an R program for the subset-based analysis of
+heterogeneous traits and disease subtypes. ASSET allows the user to search
+through all possible subsets of z-scores to identify the subset of traits
+giving the best meta-analyzed z-score. Further, it returns a p-value
+adjusting for the multiple-testing involved in the search. It also allows for
+searching for the best combination of disease subtypes associated with each
+variant.")
+ (license license:gpl2)))
+
+(define-public r-atena
+ (package
+ (name "r-atena")
+ (version "1.2.2")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "atena" version))
+ (sha256
+ (base32
+ "0b89wb7cc44c8jd6868dn8pwgid768bprkncsi87qkdz0abbhzhp"))))
+ (properties `((upstream-name . "atena")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-annotationhub
+ r-biocgenerics
+ r-biocparallel
+ r-genomeinfodb
+ r-genomicalignments
+ r-genomicranges
+ r-iranges
+ r-matrix
+ r-rsamtools
+ r-s4vectors
+ r-scales
+ r-sparsematrixstats
+ r-squarem
+ r-summarizedexperiment))
+ (native-inputs (list r-knitr))
+ (home-page "https://github.com/functionalgenomics/atena")
+ (synopsis "Analysis of transposable elements")
+ (description
+ "The atena package quantifies expression of @dfn{TEs} (transposable
+elements) from RNA-seq data through different methods, including ERVmap,
+TEtranscripts and Telescope. A common interface is provided to use each of
+these methods, which consists of building a parameter object, calling the
+quantification function with this object and getting a
+@code{SummarizedExperiment} object as an output container of the quantified
+expression profiles. The implementation allows quantifing TEs and gene
+transcripts in an integrated manner.")
+ (license license:artistic2.0)))
+
+(define-public r-atsnp
+ (package
+ (name "r-atsnp")
+ (version "1.12.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "atSNP" version))
+ (sha256
+ (base32
+ "0dmv34xqwr3l2rznapxmyrkyf1w78qzxdv88s5nn8s1m8qdkgwkz"))))
+ (properties `((upstream-name . "atSNP")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-biocfilecache
+ r-biocparallel
+ r-bsgenome
+ r-data-table
+ r-ggplot2
+ r-lifecycle
+ r-motifstack
+ r-rappdirs
+ r-rcpp
+ r-testthat))
+ (native-inputs (list r-knitr))
+ (home-page "https://github.com/sunyoungshin/atSNP")
+ (synopsis
+ "Affinity test for identifying regulatory single nucleotide polymorphisms")
+ (description
+ "The atSNP package performs affinity tests of motif matches with the
+@dfn{SNP} (single nucleotide polymorphism) or the reference genomes and
+SNP-led changes in motif matches.")
+ (license license:gpl2)))
+
+(define-public r-attract
+ (package
+ (name "r-attract")
+ (version "1.48.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "attract" version))
+ (sha256
+ (base32
+ "0f1fsv278kpnxvqg9qa5rw2k3zr8zws0ab73ldl60h6pv9cy8x82"))))
+ (properties `((upstream-name . "attract")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-annotationdbi
+ r-biobase
+ r-cluster
+ r-gostats
+ r-keggrest
+ r-limma
+ r-org-hs-eg-db
+ r-reactome-db))
+ (home-page "https://bioconductor.org/packages/attract")
+ (synopsis "Finding drivers of Kauffman's attractor landscape")
+ (description
+ "This package contains the functions to find the gene expression modules
+that represent the drivers of Kauffman's attractor landscape. The modules are
+the core attractor pathways that discriminate between different cell types of
+groups of interest. Each pathway has a set of synexpression groups, which show
+transcriptionally-coordinated changes in gene expression.")
+ (license license:lgpl2.0+)))
+
+(define-public r-awfisher
+ (package
+ (name "r-awfisher")
+ (version "1.10.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "AWFisher" version))
+ (sha256
+ (base32
+ "050k7w0azsl7rqx2pxgccihzc2q8pmh6fyy4gib2d42sdyijr2n1"))))
+ (properties `((upstream-name . "AWFisher")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-edger
+ r-limma))
+ (native-inputs (list r-knitr))
+ (home-page "https://bioconductor.org/packages/AWFisher")
+ (synopsis "Fast computing for adaptively weighted fisher's method")
+ (description
+ "This package is an implementation of the Adaptively Weighted Fisher's
+method, including fast p-value computing, variability index, and
+meta-pattern.")
+ (license license:gpl3)))
+
+(define-public r-awst
+ (package
+ (name "r-awst")
+ (version "1.4.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "awst" version))
+ (sha256
+ (base32
+ "0iw3zycmj95rmdx7f2w0j4yxkzd90y87lrzgdn9cyvvzi5avflav"))))
+ (properties `((upstream-name . "awst")))
+ (build-system r-build-system)
+ (propagated-inputs (list r-summarizedexperiment))
+ (native-inputs (list r-knitr))
+ (home-page "https://github.com/drisso/awst")
+ (synopsis "Asymmetric within-sample transformation")
+ (description
+ "This package @dfn{awst} (Asymmetric Within-Sample Transformation) that
+regularizes RNA-seq read counts and reduces the effect of noise on the
+classification of samples. AWST comprises two main steps: standardization and
+smoothing. These steps transform gene expression data to reduce the noise of
+the lowly expressed features, which suffer from background effects and low
+signal-to-noise ratio, and the influence of the highly expressed features,
+which may be the result of amplification bias and other experimental
+artifacts.")
+ (license license:expat)))
+
(define-public r-baalchip
(package
(name "r-baalchip")
rich environment of statistical and data analysis tools.")
(license license:asl2.0)))
+(define-public r-bac
+ (package
+ (name "r-bac")
+ (version "1.56.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "BAC" version))
+ (sha256
+ (base32
+ "0dkw7438d2sf6nb577dnzija54qs0nhlr47lb73li60fhlnvqmh2"))))
+ (properties `((upstream-name . "BAC")))
+ (build-system r-build-system)
+ (home-page "https://bioconductor.org/packages/BAC")
+ (synopsis "Bayesian analysis of Chip-chip experiment")
+ (description
+ "This package uses a Bayesian hierarchical model to detect enriched
+regions from ChIP-chip experiments. The common goal in analyzing this
+ChIP-chip data is to detect DNA-protein interactions from ChIP-chip
+experiments. The BAC package has mainly been tested with Affymetrix tiling
+array data. However, we expect it to work with other platforms (e.g. Agilent,
+Nimblegen, cDNA, etc.). Note that BAC does not deal with normalization, so
+you will have to normalize your data beforehand.")
+ (license license:artistic2.0)))
+
+(define-public r-bader
+ (package
+ (name "r-bader")
+ (version "1.34.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "BADER" version))
+ (sha256
+ (base32
+ "0i5x1r2ns1hxhqk5jyfqird81hck1hllvvgx5bn0rb5vl99g8spm"))))
+ (properties `((upstream-name . "BADER")))
+ (build-system r-build-system)
+ (home-page "https://bioconductor.org/packages/BADER")
+ (synopsis
+ "Bayesian analysis of differential expression in RNA sequencing data")
+ (description
+ "The BADER package is intended for the analysis of RNA sequencing data.
+The algorithm fits a Bayesian hierarchical model for RNA sequencing count
+data. BADER returns the posterior probability of differential expression for
+each gene between two groups A and B. The joint posterior distribution of the
+variables in the model can be returned in the form of posterior samples, which
+can be used for further down-stream analyses such as gene set enrichment.")
+ (license license:gpl2)))
+
+(define-public r-badregionfinder
+ (package
+ (name "r-badregionfinder")
+ (version "1.24.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "BadRegionFinder" version))
+ (sha256
+ (base32
+ "1a1pqmh5ak9s3k1lxw6flanchk24zyznwm34ixi2b78wdc3hqgm9"))))
+ (properties `((upstream-name . "BadRegionFinder")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-biomart
+ r-genomicranges
+ r-rsamtools
+ r-s4vectors
+ r-variantannotation))
+ (home-page "https://bioconductor.org/packages/BadRegionFinder")
+ (synopsis "Identifying regions with bad coverage in sequence alignment data")
+ (description
+ "BadRegionFinder is a package for identifying regions with a bad,
+acceptable and good coverage in sequence alignment data available as bam
+files. The whole genome may be considered as well as a set of target regions.
+Various visual and textual types of output are available.")
+ (license license:lgpl3)))
+
+(define-public r-bambu
+ (package
+ (name "r-bambu")
+ (version "2.2.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "bambu" version))
+ (sha256
+ (base32
+ "0dc2hpnykr575jbrq9whmdabknl70s2hcs6gkmkl4kpv7xfqdq6w"))))
+ (properties `((upstream-name . "bambu")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-biocgenerics
+ r-biocparallel
+ r-bsgenome
+ r-data-table
+ r-dplyr
+ r-genomeinfodb
+ r-genomicalignments
+ r-genomicfeatures
+ r-genomicranges
+ r-iranges
+ r-rcpp
+ r-rcpparmadillo
+ r-rsamtools
+ r-s4vectors
+ r-summarizedexperiment
+ r-tidyr
+ r-xgboost))
+ (native-inputs (list r-knitr))
+ (home-page "https://github.com/GoekeLab/bambu")
+ (synopsis
+ "Isoform reconstruction and quantification for long read RNA-Seq data")
+ (description
+ "This R package is for multi-sample transcript discovery and
+quantification using long read RNA-Seq data. You can use bambu after read
+alignment to obtain expression estimates for known and novel transcripts and
+genes. The output from bambu can directly be used for visualisation and
+downstream analysis, such as differential gene expression or transcript
+usage.")
+ (license license:gpl3)))
+
+(define-public r-bandits
+ (package
+ (name "r-bandits")
+ (version "1.12.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "BANDITS" version))
+ (sha256
+ (base32
+ "1423djb7cij68y0q2dcp8q7lrcn2fxjn6d25v4qy3w00b2w8ppg9"))))
+ (properties `((upstream-name . "BANDITS")))
+ (build-system r-build-system)
+ (propagated-inputs
+ (list r-biocparallel
+ r-data-table
+ r-doparallel
+ r-dorng
+ r-drimseq
+ r-foreach
+ r-ggplot2
+ r-mass
+ r-r-utils
+ r-rcpp
+ r-rcpparmadillo))
+ (native-inputs (list r-knitr))
+ (home-page "https://github.com/SimoneTiberi/BANDITS")
+ (synopsis "Bayesian analysis of differential splicing")
+ (description
+ "BANDITS is a Bayesian hierarchical model for detecting differential
+splicing of genes and transcripts, via @dfn{DTU} (differential transcript
+usage), between two or more conditions. The method uses a Bayesian
+hierarchical framework, which allows for sample specific proportions in a
+Dirichlet-Multinomial model, and samples the allocation of fragments to the
+transcripts. 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 "1.20.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "banocc" version))
+ (sha256
+ (base32
+ "10vaggq1w5jkxd8r2k1mhymzvb7x3h8afwn2pvmcpj022ka7xhbx"))))
+ (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 "1.4.0")
+ (source (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "barcodetrackR" version))
+ (sha256
+ (base32
+ "0yxa15xkgqazw31vq4wm8v747bw4qb18m6i602pvynk0n5bgg3d3"))))
+ (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. The required data is formed by samples and tag abundances in
+matrix form, usually from cellular barcoding experiments, integration site
+retrieval analyses, or similar technologies.")
+ (license license:cc0)))
+
(define-public r-biocversion
(package
(name "r-biocversion")
HCoop / jackhill / guix / guix.git / blobdiff