gsea_by_group: Run a GSEA by group

In amcdavid/AMmisc: Miscellaneous Functions, Templates and Tools

Description

Run a GSEA by group

Usage

gsea_by_group(
  formula,
  gene_identifier,
  data,
  set_list,
  nperm = 500,
  maxSize = 500,
  ...
)

## S3 method for class 'GroupedGSEA'
as.data.frame(
  x,
  row.names = NULL,
  optional = TRUE,
  ...,
  topn = Inf,
  wrap_len = 30,
  p.adjust_method = "BH"
)

## S3 method for class 'GroupedGSEA'
plot(x, ..., topn = 5, wrap_len = 30, p.adjust_method = "BH")

Arguments

formula	a formula of the kind numeric_score ~ group1 + group2 + ... identifying the column containing the score vs the grouping variables, which will be interacted with each other
gene_identifier	character
data	data.frame in which the formula and gene_identifer are interpreted
set_list	alternatively, a list of named and sorted input
nperm	Number of permutations to do. Minimial possible nominal p-value is about 1/nperm
maxSize	Maximal size of a gene set to test. All pathways above the threshold are excluded.
...	passed to fgsea::fgsea()
x	object of class GroupedGSEA
row.names	ignored
optional	ignored
topn	report at least this many pathways (by minimum p value across groups)
wrap_len	wrap pathway titles after this many characters
p.adjust_method	passed to stats::p.adjust()

Value

an object of class GroupedGSEA, which is internally just a list fgsea::fgsea() objects.

Methods (by generic)

• as.data.frame: coerce result to a data.frame

• plot: make a plot of the results

Examples

data(exampleRanks, package = 'fgsea')
data(examplePathways, package = 'fgsea')
data = data.frame(score = exampleRanks, gene = names(exampleRanks), treatment = rep(c('A', 'B'), length.out = length(exampleRanks)))
gout = gsea_by_group(score ~ treatment, 'gene', data, pathways = examplePathways)
df = as.data.frame(gout)
plot(gout)

amcdavid/AMmisc documentation built on June 1, 2020, 11:04 a.m.