[ Source: r-bioc-gsva ]
Paketti: r-bioc-gsva (1.46.0+ds-1)
Links for r-bioc-gsva
Debian-palvelut:
Imuroi lähdekoodipaketti r-bioc-gsva:
- [r-bioc-gsva_1.46.0+ds-1.dsc]
- [r-bioc-gsva_1.46.0+ds.orig.tar.xz]
- [r-bioc-gsva_1.46.0+ds-1.debian.tar.xz]
Ylläpitäjät:
External Resources:
- Kotisivu [bioconductor.org]
Samankaltaisia paketteja:
Gene Set Variation Analysis for microarray and RNA-seq data
Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene- set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross- tissue pathway analysis, in a pathway-centric manner.
Muut pakettiin r-bioc-gsva liittyvät paketit
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- dep: libc6 (>= 2.4)
- GNU-C-kirjasto: jaetut kirjastot
myös näennäispaketti, jonka toteuttaa libc6-udeb
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- dep: r-api-4.0
- näennäispaketti, jonka toteuttaa r-base-core
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- dep: r-api-bioc-3.16
- näennäispaketti, jonka toteuttaa r-bioc-biocgenerics
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- dep: r-base-core (>= 4.2.2.20221110-1)
- GNU R core of statistical computation and graphics system
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- dep: r-bioc-biobase
- base functions for Bioconductor
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- dep: r-bioc-biocparallel
- BioConductor facilities for parallel evaluation
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- dep: r-bioc-biocsingular
- Singular Value Decomposition for Bioconductor Packages
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- dep: r-bioc-delayedarray
- BioConductor delayed operations on array-like objects
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- dep: r-bioc-delayedmatrixstats
- Functions on Rows and Columns of 'DelayedMatrix' Objects
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- dep: r-bioc-gseabase
- Gene set enrichment data structures and methods
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- dep: r-bioc-hdf5array
- HDF5 backend for DelayedArray objects
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- dep: r-bioc-iranges
- GNU R low-level containers for storing sets of integer ranges
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- dep: r-bioc-s4vectors
- BioConductor S4 implementation of vectors and lists
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- dep: r-bioc-singlecellexperiment
- S4 Classes for Single Cell Data
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- dep: r-bioc-sparsematrixstats
- BioConductor summary statistics for rows and columns of sparse matrices
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- dep: r-bioc-summarizedexperiment
- BioConductor assay container
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- dep: r-cran-matrix (>= 1.5-0)
- GNU R package of classes for dense and sparse matrices
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- rec: r-cran-fastmatch
- GNU R package for fast match replacement for repeated look-ups
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- rec: r-cran-runit
- GNU R package providing unit testing framework
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- sug: r-bioc-biocgenerics
- generic functions for Bioconductor
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- sug: r-bioc-biocstyle
- standard styles for vignettes and other Bioconductor documents
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- sug: r-bioc-edger
- Empirical analysis of digital gene expression data in R
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- sug: r-bioc-genefilter
- methods for filtering genes from microarray experiments
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- sug: r-bioc-limma
- linear models for microarray data
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- sug: r-bioc-org.hs.eg.db
- genome-wide annotation for Human
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- sug: r-cran-data.table
- GNU R extension of Data.frame
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- sug: r-cran-future
- R package: A Future API for R
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- sug: r-cran-ggplot2
- implementation of the Grammar of Graphics
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- sug: r-cran-knitr
- GNU R package for dynamic report generation using Literate Programming
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- sug: r-cran-plotly
- create interactive web graphics via 'plotly.js' in GNU R
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- sug: r-cran-promises
- GNU R abstractions for promise-based asynchronous programming
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- sug: r-cran-rcolorbrewer
- GNU R package providing suitable color palettes
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- sug: r-cran-rmarkdown
- convert R markdown documents into a variety of formats
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- sug: r-cran-shiny
- GNU R web application framework
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- sug: r-cran-shinydashboard
- GNU R create dashboards with 'Shiny'
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- sug: r-cran-shinyjs
- Easily Improve the User Experience of Your Shiny Apps in Seconds
Imuroi r-bioc-gsva
| Arkkitehtuuri | Paketin koko | Koko asennettuna | Tiedostot |
|---|---|---|---|
| amd64 | 781.2 kt | 912.0 kt | [tiedostoluettelo] |