Gsea Prerank Tools¶
Configuration File: gsea_prerank_tools.json
Tool Type: Local
Tools Count: 1
This page contains all tools defined in the gsea_prerank_tools.json configuration file.
Available Tools¶
GSEA_prerank (Type: GSEAPrerankTool)¶
Pre-ranked Gene Set Enrichment Analysis (Subramanian 2005) on a ranked gene list (e.g. genes rank…
GSEA_prerank tool specification
Tool Information:
Name:
GSEA_prerankType:
GSEAPrerankToolDescription: Pre-ranked Gene Set Enrichment Analysis (Subramanian 2005) on a ranked gene list (e.g. genes ranked by a DESeq2/edgeR statistic) against one or more gene sets. Returns per-set enrichment score (ES), normalized ES (NES), permutation p-value, and leading-edge genes. Pure-compute (no R, no bundled MSigDB - supply gene sets, e.g. from Enrichr). Complements over-representation tools by using the full ranking.
Parameters:
ranked_genes([‘object’, ‘null’]) (optional) {gene: score} mapping (score = DE statistic / fold change). Genes are ranked by score descending. Alternative to genes+scores.genes([‘array’, ‘null’]) (optional) Gene identifiers (use with scores, same order).scores([‘array’, ‘null’]) (optional) Per-gene ranking metric (same order as genes).gene_sets([‘object’, ‘null’]) (optional) {set_name: [gene, …]} collection to test. Alternative to gene_set.gene_set([‘array’, ‘null’]) (optional) A single gene set (list of gene symbols).weight([‘number’, ‘null’]) (optional) Score weighting exponent for the running sum (default 1.0; classic GSEA).n_permutations([‘integer’, ‘null’]) (optional) Gene-label permutations for the p-value (default 1000).
Example Usage:
query = {
"name": "GSEA_prerank",
"arguments": {
}
}
result = tu.run(query)