mitch_calc: mitch_calc

In markziemann/mitch: Multi-Contrast Gene Set Enrichment Analysis

mitch_calc

Description

This function performs multivariate gene set enrichment analysis.

Usage

mitch_calc(
  x,
  genesets,
  minsetsize = 10,
  cores = 1,
  resrows = 50,
  priority = NULL
)

Arguments

x	a multicolumn numerical table with each column containing differential expression scores for a contrast. Rownames must match genesets.
genesets	lists of genes imported by the gmt_imprt function or similar.
minsetsize	the minimum number of genes required in a set for it to be included in the statistical analysis. Default is 10.
cores	the number of parallel threads for computation. Defaults to 1.
resrows	an integer value representing the number of top genesets for which a detailed report is to be generated. Default is 50.
priority	the prioritisation metric used to selecting top gene sets. Valid options are 'significance', 'effect' and 'SD'.

Value

mitch res object with the following parts: $input_profile: the supplied input differential profile $input_genesets: the supplied input gene sets $ranked_profile: the differential profile after ranking $enrichment_result: the table of MANOVA/ANOVA enrichment results for each gene set $analysis_metrics: several metrics that are important to the interpretation of the results $detailed_sets: a list of dataframes containing ranks of members of prioritised gene sets.

Examples

# Example using mitch to calculate multivariate enrichments and
# prioritise based on effect size 
data(myImportedData,genesetsExample)
resExample<-mitch_calc(myImportedData,genesetsExample,priority='effect',
minsetsize=5,cores=2)

markziemann/mitch documentation built on Nov. 3, 2024, 7:28 p.m.