Paket: r-bioc-gsva (1.52.3+ds-1)

[ Quellcode: r-bioc-gsva  ]

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.

Andere Pakete mit Bezug zu r-bioc-gsva

• dep: libc6 (>= 2.17)

  GNU-C-Bibliothek: Laufzeitbibliotheken
  auch ein virtuelles Paket, bereitgestellt durch libc6-udeb

• dep: r-api-4.0

  virtuelles Paket, bereitgestellt durch r-base-core

• dep: r-api-bioc-3.19

  virtuelles Paket, bereitgestellt durch r-bioc-biocgenerics

• dep: r-bioc-biobase (>= 2.64.0)

  base functions for Bioconductor

• dep: r-bioc-biocparallel (>= 1.38.0)

  BioConductor facilities for parallel evaluation

• dep: r-bioc-biocsingular (>= 1.20.0)

  Singular Value Decomposition for Bioconductor Packages

• dep: r-bioc-delayedarray (>= 0.30.1)

  BioConductor delayed operations on array-like objects

• dep: r-bioc-delayedmatrixstats (>= 1.26.0)

  Functions on Rows and Columns of 'DelayedMatrix' Objects

• dep: r-bioc-gseabase (>= 1.66.0)

  Gene set enrichment data structures and methods

• dep: r-bioc-hdf5array (>= 1.32.0)

  HDF5 backend for DelayedArray objects

• dep: r-bioc-iranges (>= 2.38.1)

  GNU R low-level containers for storing sets of integer ranges

• dep: r-bioc-s4vectors (>= 0.42.1)

  BioConductor S4 implementation of vectors and lists

• dep: r-bioc-singlecellexperiment (>= 1.26.0)

  S4 Classes for Single Cell Data

• dep: r-bioc-sparsematrixstats (>= 1.16.0)

  BioConductor summary statistics for rows and columns of sparse matrices

• dep: r-bioc-spatialexperiment (>= 1.14.0)

  S4 Class for Spatially Resolved -omics Data

• dep: r-bioc-summarizedexperiment (>= 1.34.0)

  BioConductor assay container

• dep: r-cran-matrix (>= 1.5-0)

  GNU R - Paket von Klassen für dicht und dünn besetzte Matrizen

• sug: r-bioc-biocgenerics (>= 0.50.0)

  generic functions for Bioconductor

• sug: r-bioc-biocstyle (>= 2.32.1)

  standard styles for vignettes and other Bioconductor documents

• sug: r-bioc-edger (>= 4.2.0)

  Empirische Analyse von digitalen Genexpressionsdaten mit R

• sug: r-bioc-genefilter (>= 1.86.0)

  methods for filtering genes from microarray experiments

• sug: r-bioc-gsvadata (>= 1.40.0)

  Data employed in the vignette of the GSVA package

• sug: r-bioc-limma (>= 3.60.3)

  linear models for microarray data

• sug: r-bioc-org.hs.eg.db (>= 3.19.1-1)

  genome-wide annotation for Human

• sug: r-cran-data.table

  GNU R - Erweiterung von data.frame()

• sug: r-cran-future

  R package: A Future API for R

• sug: r-cran-ggplot2

  Implementierung der »Grammar of Graphics«

• sug: r-cran-knitr

  GNU R package for dynamic report generation using Literate Programming

• sug: r-cran-plotly

  create interactive web graphics via 'plotly.js' in GNU R

• sug: r-cran-promises

  GNU-R-Abstraktionen für asynchrone Programmierung auf Basis von Promises

• sug: r-cran-rcolorbrewer

  GNU R package providing suitable color palettes

• sug: r-cran-rmarkdown

  Konvertierung von R-Markdown-Dokumenten in verschiedene Formate

• sug: r-cran-runit

  GNU-R-Paket, das ein Programmiergerüst für Komponententests bereitstellt

• sug: r-cran-shiny

  GNU R web application framework

• sug: r-cran-shinydashboard

  GNU R create dashboards with 'Shiny'

• sug: r-cran-shinyjs

  Easily Improve the User Experience of Your Shiny Apps in Seconds

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Architektur	Paketgröße	Größe (installiert)	Dateien
arm64	1.086,2 kB	1.366,0 kB	[Liste der Dateien]