sear: Simple enrichment analysis in R using the MSigDB collections.

In cashoes/sear: Simple (effin') enrichment analysis in R

Simple enrichment analysis in R using the MSigDB collections.

Description

Carry out enrichment analysis against some or all of the MSigDB collections (1), Blood Transcriptome genes (2) and Tissue Enrichment Sets (3).

Usage

sear(
  input,
  type = c("mrna", "mirna"),
  return_members = F,
  return_intersect = T
)

Arguments

input	A character vector of HUGO gene naming commitee (HGNC) gene symbols.
type	A character string. The type of symbols in the input: 'mrna' for gene symbols, 'mirna' for miRNAs. The reference gene sets used differ for either types. See: Godard, P., and van Eyll, J. (2015). Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy. Nucl. Acids Res. 43, 3490-3497.
return_members	A logical. Whether to include a list-column in the return object containing the gene set member genes.
return_intersect	A logical. Whether to include a list-column in the return object containing the genes found in common between the gene set and the input.

Details

A list of genes is compared to each annotated gene set in turn by performing a hypergeometric test of the overlap. The size of the input gene list, gene set, intersection and resulting p-value are returned. P-values can be adjusted over each collection (optimistic) or globally (pessimistic), using any of the methods available to 'p/adjust()'.

Examples

library(dplyr)
data('collections')
input <- collections$members_mrna %>% unlist() %>% unique() %>% sample(100)
output <- sear(input, type = 'mrna') %>%
  arrange(fdr) %>%
  slice(1:100)

cashoes/sear documentation built on Feb. 16, 2024, 6:45 a.m.