PLAID ultrafast gene set enrichment scoring

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Documentation for package ‘plaid’ version 0.99.19

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

Help Pages

chunked_crossprod	Chunked computation of cross product
colranks	Compute columnwise ranks of matrix
cor_sparse_matrix	Calculate sparse correlation matrix handling missing values
dualGSEA	Reimplementation of dualGSEA (Bull et al., 2024) but defaults with replaid backend. For the preranked test we still use fgsea. Should be much faster than original using fgsea + GSVA::ssGSEA.
fc_ttest	T-test statistical testing of differentially enrichment
fc_ztest	Z-test statistical testing of differentially enrichment
gmt2mat	Convert GMT to Binary Matrix
gset.rankcor	Calculate gene set rank correlation
gset_averageCLR	Compute geneset expression as the average log-ration of genes in the geneset. Requires log-expression matrix X and (sparse) geneset matrix matG.
gset_ttest	Perform t-test on gene set scores
mat.rowsds	Calculate row standard deviations for matrix
mat2gmt	Convert Binary Matrix to GMT
matrix_metap	Matrix version for combining p-values using fisher or stouffer method. Much faster than doing metap::sumlog() and metap::sumz()
matrix_onesample_ttest	Perform one-sample t-test on matrix with gene sets
normalize_medians	Normalize column medians of matrix
plaid	Compute PLAID single-sample enrichment score
read.gmt	Read GMT File
replaid.aucell	Fast calculation of AUCell
replaid.gsva	Fast approximation of GSVA
replaid.scse	Fast calculation of scSE score
replaid.sing	Fast calculation of singscore
replaid.ssgsea	Fast calculation of ssGSEA
replaid.ucell	Fast calculation of UCell
sparse_colranks	Compute columm ranks for sparse matrix. Internally used by colranks()
write.gmt	Write GMT File