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Find consensus pathways across studies (vote counting)

Source: R/06_pathway.R
mx_pathway_consensus.Rd

Counts in how many per-study enrichment analyses each pathway is significant. Vote counting ignores effect size and is less powerful than mx_pathway_studies; use it as a descriptive summary.

Usage

mx_pathway_consensus(
  pathway_results,
  min_fraction = 0.5,
  padj_threshold = 0.05
)

Arguments

pathway_results

A list of per-study enrichment data.frames with columns pathway_id and padj, e.g. attr(mx_pathway_studies(...), "per_study").

min_fraction

Numeric. Minimum fraction of studies in which a pathway must be significant. Default: 0.5.

padj_threshold

Numeric. Significance threshold per study. Default: 0.05.

Value

A data.frame with pathway_id, n_significant_studies and fraction_studies.

See also

mx_pathway_studies

Examples

pr1 <- data.frame(pathway_id = c("A", "B"), padj = c(0.01, 0.2))
pr2 <- data.frame(pathway_id = c("A", "B"), padj = c(0.03, 0.01))
mx_pathway_consensus(list(pr1, pr2), min_fraction = 1)
#>   pathway_id n_significant_studies fraction_studies
#> 1          A                     2                1