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

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Documentation for package ‘pcaExplorer’ version 2.24.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

correlatePCs	Principal components (cor)relation with experimental covariates
distro_expr	Plot distribution of expression values
geneprofiler	Extract and plot the expression profile of genes
genespca	Principal components analysis on the genes
get_annotation	Get an annotation data frame from biomaRt
get_annotation_orgdb	Get an annotation data frame from org db packages
hi_loadings	Extract genes with highest loadings
limmaquickpca2go	Functional interpretation of the principal components, based on simple overrepresentation analysis
makeExampleDESeqDataSet_multifac	Make a simulated DESeqDataSet for two or more experimental factors
pair_corr	Pairwise scatter and correlation plot of counts
pca2go	Functional interpretation of the principal components
pcaExplorer	Explore a dataset from a PCA perspective
pcaExplorer-pkg	pcaExplorer: analyzing time-lapse microscopy imaging, from detection to tracking
pcaplot	Sample PCA plot for transformed data
pcaplot3d	Sample PCA plot for transformed data
pcascree	Scree plot of the PCA on the samples
plotPCcorrs	Plot significance of (cor)relations of covariates VS principal components
topGOtable	Extract functional terms enriched in the DE genes, based on topGO