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

## Documentation for package ‘pcaExplorer’ version 2.16.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## 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