# PLAID ultrafast gene set enrichment scoring

## Documentation for package ‘plaid’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## 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