pinnacle: Evaluate Gene Set Analysis with Pinnacle

In GabrielHoffman/pinnacle: Gene set analysis accounting for gene-gene correlations

Evaluate Gene Set Analysis with Pinnacle

Description

Perform Gene Set Analysis (GSA) by comparing t-statistics from a given gene set to genome-wide t-statistics, while accounting for co-expression structure

Usage

pinnacle(
  fit,
  coef,
  geneSets,
  data,
  formula = ~1,
  setSize = c(10, 5000),
  quiet = FALSE,
  ...
)

Arguments

fit	regression model fit by limma::lmFit() or variancePartition::dream()
coef	indicate coefficient or contrast to be extracted from fit using topTable
geneSets	GeneSetCollection from GSEABase
data	data.frame storing properties of each gene, with rownames being gene names
formula	formula specifying covariates in regression using t-statistics as response
setSize	array of two elements specifying the min and max number of genes allowed in a gene set. Only gene sets satisfying these criteria are retained
quiet	suppresss messages
...	other arguments passed to lm_each_eclairs() and then lm

Value

data.frame with results for each gene set

GabrielHoffman/pinnacle documentation built on May 29, 2022, 8 p.m.