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Bioconductor - GSVA

GSVA is a Bioconductor package that transforms gene by sample matrices into gene-set by sample matrices, allowing pathway enrichment evaluation for each sample. Learn how to install, use and cite GSVA for microarray and RNA-Seq data analysis.

GSVA: gene set variation analysis - Bioconductor

GSVA is a method for pathway-centric analysis of molecular data by performing gene set enrichment on single samples. Learn how to install, use and customize the GSVA package with R and Bioconductor.

GSVA: gene set variation analysis for microarray and RNA-Seq data

GSVA is a non-parametric, unsupervised method that estimates variation of pathway activity over a sample population in an expression profile. It can be applied to microarray and RNA-seq data and can be used for differential pathway activity and survival analysis.

GitHub - rcastelo/GSVA: Gene set variation analysis

GSVA transforms gene by sample matrices into gene-set by sample matrices, allowing pathway enrichment evaluation for each sample. Learn how to install, cite and use GSVA for microarray and RNA-seq data, and contribute to its development.

GSVA: gene set variation analysis for microarray and RNA-seq data

GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. M …

Gene Set Variation Analysis - Dave Tang's blog

Learn how to use GSVA, a method for single-sample gene set enrichment analysis, on bulk RNA-seq data. See examples of GSVA implementation, results and comparison with GSEA.

GSVA: gene set variation analysis - GitHub Pages

GSVA is a method to calculate pathway enrichment scores for each sample based on gene expression data. It can be applied to microarray and RNA-seq data, and used for pathway-centric analyses such as differential expression, survival prediction, or clustering.

Biomarker Exploration (Gene Set Variation Analysis; GSVA)

Gene Set Variation Analysis (GSVA) is a method used to estimate the activity of biological pathways in each individual sample based on gene expression data.

gsva : Gene Set Variation Analysis - R Package Documentation

expr: Gene expression data which can be given either as a SummarizedExperiment or ExpressionSet object, or as a matrix of expression values where rows correspond to genes and columns correspond to samples. gset.idx.list: Gene sets provided either as a list object or as a GeneSetCollection object.. annotation: In the case of calling gsva() on a SummarizedExperiment object, the annotation ...

Package 'GSVA' reference manual

GSVA is a method for estimating variation of gene set enrichment through the samples of a microarray or RNA-Seq data set. Learn how to use GSVA functions to compute gene-sets overlap, handle duplicated gene set names, filter gene sets, retrieve or determine gene sets, and more.

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