Skip to content

Prepare GSEA Specifications

Process Details

  • Name: Prepare GSEA
  • Process UUID: db6e0le3h9iziz9p58j1pbrnborg5o
  • Process Group: Gene Set Enrichment

Overview

This process runs Gene Set Enrichment Analysis (GSEA) on differential expression results to identify significantly enriched biological pathways and gene sets. The analysis uses pre-ranked gene lists to determine whether members of specific gene sets are randomly distributed throughout the ranked list or primarily found at the top or bottom, indicating coordinated regulation.

This process is implemented in Bash, which invokes a Python script for GSEA analysis and pathway enrichment calculations.

Key Functionality

  • Gene Set Enrichment Analysis: Performs GSEA using pre-ranked gene lists from differential expression analysis
  • Multi-Database Support: Supports analysis using multiple MSigDB collections (Hallmark, Curated, Ontology, etc.)
  • Species-Specific Analysis: Handles both human and mouse gene sets with appropriate symbol mapping
  • Statistical Filtering: Applies user-defined thresholds for normalized enrichment scores and adjusted p-values
  • Comprehensive Reporting: Generates detailed enrichment results and pathway visualization outputs

Input/Output Specification

Inputs

Required Inputs

  • ranked_list

    • Description: Pre-ranked gene list from differential expression analysis containing gene symbols and fold change values
    • Format: TSV file

  • run_GSEA

    • Description: Boolean flag to control whether GSEA analysis should be executed
    • Format: Boolean value

Optional Inputs

  • postfix
    • Description: Optional suffix to append to output filenames for organizational purposes
    • Format: Text string

Outputs

  • outputFile

    • Description: GSEA enrichment results containing pathway names, enrichment scores, p-values, and gene set details
    • Format: TSV file

  • GSEA Reports

    • Description: Comprehensive GSEA analysis outputs including visualization files and detailed pathway reports
    • Format: Directory structure with multiple file types

Parameters & Settings

These parameters can be adjusted in the Foundry UI when running this process.

  • Feature Column

    • Description: Column name containing gene identifiers in the input file
    • Default value: gene

  • Rank Column

    • Description: Column name containing ranking values (typically log2 fold changes) for gene prioritization
    • Default value: log2FoldChange_shrink

  • Species

    • Description: Only human and mouse are currently supported. The input only controls which gene sets are displayed below. It does not affect pipeline behavior.
    • Available options: human (default), mouse

  • H: Hallmark

    • Description: Include Hallmark gene sets representing well-defined biological states or processes
    • Default value: true

  • C1: Positional

    • Description: Include gene sets for each human chromosome and cytogenetic band
    • Default value: false

  • C2: Curated

    • Description: Include curated gene sets from online pathway databases, publications, and domain experts
    • Default value: false

  • C2-CGP: Chemical and Genetic Perturbations

    • Description: Include gene sets representing expression signatures of chemical and genetic perturbations
    • Default value: false

  • C2-CP: Canonical Pathways

    • Description: Include canonical representations of biological processes compiled from pathway databases
    • Default value: false

  • C3-MIR: microRNA Targets

    • Description: Include gene sets containing genes that share a microRNA binding motif
    • Default value: false

  • C3-TFT: Transcription Factor Targets

    • Description: Include gene sets containing genes that share a transcription factor binding site
    • Default value: false

  • C4: Computational

    • Description: Include gene sets defined by mining large collections of cancer-oriented microarray data
    • Default value: false

  • C4-CGN: Cancer Gene Neighborhoods

    • Description: Include gene sets defined by expression neighborhoods centered on cancer-associated genes
    • Default value: false

  • C4-CM: Cancer Modules

    • Description: Include gene sets defined by co-expression modules from cancer microarray data
    • Default value: false

  • C5: Ontology

    • Description: Include gene sets derived from the Gene Ontology project
    • Default value: false

  • C5-GO: Gene Ontology

    • Description: Include all Gene Ontology gene sets
    • Default value: false

  • C5-GO-BP: GO Biological Processes

    • Description: Include Gene Ontology Biological Process gene sets
    • Default value: false

  • C5-GO-CC: GO Cellular Components

    • Description: Include Gene Ontology Cellular Component gene sets
    • Default value: false

  • C5-GO-MF: GO Molecular Functions

    • Description: Include Gene Ontology Molecular Function gene sets
    • Default value: false

  • C5-HPO: Human Phenotype Ontology

    • Description: Include gene sets derived from the Human Phenotype Ontology
    • Default value: false

  • C6: Oncogenic

    • Description: Include gene sets representing signatures of oncogenic pathways
    • Default value: false

  • C7: Immunologic

    • Description: Include gene sets representing cell states and perturbations within the immune system
    • Default value: false

  • C8: Cell Type Signature

    • Description: Include gene sets containing cluster markers identified from single-cell sequencing studies
    • Default value: false

  • MH: Hallmark

    • Description: Include mouse Hallmark gene sets representing well-defined biological states or processes
    • Default value: true

  • M1: Positional

    • Description: Include gene sets for each mouse chromosome and cytogenetic band
    • Default value: false

  • M2: Curated

    • Description: Include mouse curated gene sets from online pathway databases and publications
    • Default value: false

  • M2-CGP: Chemical and Genetic Perturbations

    • Description: Include mouse gene sets representing expression signatures of chemical and genetic perturbations
    • Default value: false

  • M2-CP: Canonical Pathways

    • Description: Include mouse canonical representations of biological processes
    • Default value: false

  • M3-GTRD: Transcription Factor Targets

    • Description: Include mouse gene sets containing genes that share transcription factor binding sites from GTRD
    • Default value: false

  • M3-miRDB: microRNA Targets

    • Description: Include mouse gene sets containing genes that share microRNA binding motifs from miRDB
    • Default value: false

  • M5: Ontology

    • Description: Include mouse gene sets derived from the Gene Ontology project
    • Default value: false

  • M5-GO: Gene Ontology

    • Description: Include all mouse Gene Ontology gene sets
    • Default value: false

  • M5-GO-BP: GO Biological Processes

    • Description: Include mouse Gene Ontology Biological Process gene sets
    • Default value: false

  • M5-GO-CC: GO Cellular Components

    • Description: Include mouse Gene Ontology Cellular Component gene sets
    • Default value: false

  • M5-GO-MF: GO Molecular Functions

    • Description: Include mouse Gene Ontology Molecular Function gene sets
    • Default value: false

  • M5-MPT: Phenotype Ontology

    • Description: Include mouse gene sets derived from the Mammalian Phenotype Ontology
    • Default value: false

  • M8: Cell Type Signature

    • Description: Include mouse gene sets containing cluster markers from single-cell sequencing studies
    • Default value: false

  • Minimal Gene Set Size

    • Description: Minimum number of genes required in a gene set for inclusion in analysis
    • Default value: 1

  • Maximal Gene Set Size

    • Description: Maximum number of genes allowed in a gene set for inclusion in analysis
    • Default value: 10000

  • NES cutoff

    • Description: Normalized Enrichment Score threshold required to be considered significant
    • Default value: 1

  • Adjusted p-value cutoff

    • Description: Adjusted p-value significance threshold required to be considered significant
    • Default value: 0.05

  • Seed

    • Description: Random seed for reproducible results across multiple runs
    • Default value: 1

References & Resources

  • Tool Documentation: Contact the team for details on prepare_GSEA.py
  • Related Papers: Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S., & Mesirov, J.P. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43), 15545-15550. DOI: 10.1073/pnas.0506580102