Пакет: r-bioc-gsva (1.46.0+ds-1)

Връзки за r-bioc-gsva

Ресурси за Debian:

Изтегляне на пакет-източник r-bioc-gsva.

Отговорници:

Външни препратки:

Начална страница [bioconductor.org]

Подобни пакети:

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.

Други пакети, свързани с r-bioc-gsva

зависимости

препоръчани

предложени

enhances

dep: libc6 (>= 2.4)

GNU C Library: Shared libraries
също и виртуален пакет, предлаган от libc6-udeb
dep: r-api-4.0

виртуален пакет, предлаган от r-base-core
dep: r-api-bioc-3.16

виртуален пакет, предлаган от r-bioc-biocgenerics
dep: r-base-core (>= 4.2.2.20221110-1)

GNU R core of statistical computation and graphics system
dep: r-bioc-biobase

base functions for Bioconductor
dep: r-bioc-biocparallel

BioConductor facilities for parallel evaluation
dep: r-bioc-biocsingular

Singular Value Decomposition for Bioconductor Packages
dep: r-bioc-delayedarray

BioConductor delayed operations on array-like objects
dep: r-bioc-delayedmatrixstats

Functions on Rows and Columns of 'DelayedMatrix' Objects
dep: r-bioc-gseabase

Gene set enrichment data structures and methods
dep: r-bioc-hdf5array

HDF5 backend for DelayedArray objects
dep: r-bioc-iranges

GNU R low-level containers for storing sets of integer ranges
dep: r-bioc-s4vectors

BioConductor S4 implementation of vectors and lists
dep: r-bioc-singlecellexperiment

S4 Classes for Single Cell Data
dep: r-bioc-sparsematrixstats

BioConductor summary statistics for rows and columns of sparse matrices
dep: r-bioc-summarizedexperiment

BioConductor assay container
dep: r-cran-matrix (>= 1.5-0)

GNU R package of classes for dense and sparse matrices

rec: r-cran-fastmatch

GNU R package for fast match replacement for repeated look-ups
rec: r-cran-runit

GNU R package providing unit testing framework

sug: r-bioc-biocgenerics

generic functions for Bioconductor
sug: r-bioc-biocstyle

standard styles for vignettes and other Bioconductor documents
sug: r-bioc-edger

Empirical analysis of digital gene expression data in R
sug: r-bioc-genefilter

methods for filtering genes from microarray experiments
sug: r-bioc-limma

linear models for microarray data
sug: r-bioc-org.hs.eg.db

genome-wide annotation for Human
sug: r-cran-data.table

GNU R extension of Data.frame
sug: r-cran-future

R package: A Future API for R
sug: r-cran-ggplot2

implementation of the 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 abstractions for promise-based asynchronous programming
sug: r-cran-rcolorbrewer

GNU R package providing suitable color palettes
sug: r-cran-rmarkdown

convert R markdown documents into a variety of formats
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

Изтегляне на r-bioc-gsva

Изтегляне за всички налични архитектури
Архитектура	Големина на пакета	Големина след инсталиране	Файлове
amd64	781,2 кБ	912,0 кБ	[списък на файловете]