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pcaExplorer (version 1.0.2)

Interactive Visualization of RNA-seq Data Using a Principal Components Approach

Description

This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.

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Version

Version

1.0.2

License

MIT + file LICENSE

Issues

7

Pull Requests

0

Stars

56

Forks

17

Maintainer

Federico Marini

Last Published

February 15th, 2017

Functions in pcaExplorer (1.0.2)

limmaquickpca2go

Functional interpretation of the principal components, based on simple overrepresentation analysis
pcaExplorer

pcaExplorer: analyzing time-lapse microscopy imaging, from detection to tracking
pca2go

Functional interpretation of the principal components
makeExampleDESeqDataSet_multifac

Make a simulated DESeqDataSet for two or more experimental factors
plotPCcorrs

Plot significance of (cor)relations of covariates VS principal components
topGOtable

Extract functional terms enriched in the DE genes, based on topGO
correlatePCs

Principal components (cor)relation with experimental covariates
genespca

Principal components analysis on the genes
pcaplot

Sample PCA plot for transformed data
hi_loadings

Extract genes with highest loadings
pcascree

Scree plot of the PCA on the samples