Generate principal component analysis data that can be used in downstream analyses.
generatePCs(mat, vars, nFeatures)
Arguments
- mat
A data matrix where rows are features and columns are samples
- vars
A vector of gene variances (can calculate using RGenEDA::plotVariance)
- nFeatures
Number of top features to generate principal components on.
Value
A list consisting of 3 slots: Loadings, Eigenvectors, and percent_var