https://github.com/animesh/gsea

Replicate: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles https://www.pnas.org/doi/10.1073/pnas.0506580102

https://github.com/animesh/gsea

Science Score: 39.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Replicate: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles https://www.pnas.org/doi/10.1073/pnas.0506580102

Basic Info
  • Host: GitHub
  • Owner: animesh
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 653 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 11 months ago · Last pushed 11 months ago
Metadata Files
Readme License

README.md

Trying to Replicate GSEA: Subramanian et al. (2005)

This project is trying to replicate the Gene Set Enrichment Analysis (GSEA) methodology as described in the landmark article:

  • Subramanian, A., Tamayo, P., Mootha, V.K., et al. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. PNAS, 102(43), 15545-15550. https://www.pnas.org/doi/10.1073/pnas.0506580102

Data Sources

All data used in this project are publicly available from the Broad Institute's GSEA/MSigDB resource: - GSEA Example Datasets: https://www.gsea-msigdb.org/gsea/datasets.jsp

Specifically, for the leukemia analysis: - Expression data: Leukemia_hgu95av2.gct - Gene sets: c2.symbols.gmt

Workflow

  1. Compute a ranked gene list using the signal-to-noise ratio between ALL and AML samples from the leukemia dataset.
  2. Run a from-scratch GSEA pre-ranked analysis using the ranked list and the C2 (curated) gene sets.
  3. Compare results to those reported in the original GSEA article.

Current Issue

All tested gene sets return ES=0 and p=1.0. This likely indicates a mismatch between gene symbols in the ranked list and those in the gene sets, or another data integration issue. Resolving this is a current priority for the project.

Files

  • compute_snr_ranked_list.py: Computes the signal-to-noise ratio ranked gene list from the .gct and .cls files.
  • gsea_preranked_with_fdr_and_plot.py: Runs the GSEA pre-ranked analysis and outputs results and enrichment plots.
  • leukemia_ranked_gene_list.txt: Ranked gene list for GSEA.
  • gsea_preranked_results_with_fdr.csv: GSEA results (ES, p-value, FDR/q-value).
  • gsea_plots/: Enrichment plots for selected gene sets.

References

Owner

  • Name: Ani
  • Login: animesh
  • Kind: user
  • Location: Norway
  • Company: Norwegian University of Science and Technology

A medical graduate from Delhi University with post-graduation in bioinformatics from Jawaharlal Nehru University, India.

GitHub Events

Total
  • Push event: 1
  • Create event: 2
Last Year
  • Push event: 1
  • Create event: 2