Analysis Summary

Summary

Functional analysis can be a powerful tool for summarizing differential expression results from a variety of experiments, including both bulk and single-cell RNA-seq.

What we’ve accomplished:

• Discussed the concepts behind ORA, GSEA, and Pathway Topology approaches to functional enrichment approaches.
• Used a web-browser tool to perform ORA analysis of bulk RNA-seq data.
  
• Used R/RStudio and WebGestaltR to run ORA for bulk RNA-seq data in a more reproducible manner.
  
• Used WebGestaltR to run GSEA for single-cell RNA-seq data
  
• Created customized visualizations at the gene and term level
  
• Reviewed biological knowledge bases commonly used in functional analyses.

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Resources

Methods and Approaches

• Khatri P, Sirota M, Butte AJ. Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol. 2012;8(2):e1002375. doi:10.1371/journal.pcbi.1002375 https://pubmed.ncbi.nlm.nih.gov/22383865/

• Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545-15550. doi:10.1073/pnas.0506580102
  https://pmc.ncbi.nlm.nih.gov/articles/PMC1239896/

• Wijesooriya K, Jadaan SA, Perera KL, Kaur T, Ziemann M. Urgent need for consistent standards in functional enrichment analysis. PLoS Comput Biol. 2022;18(3):e1009935. Published 2022 Mar 9. doi:10.1371/journal.pcbi.1009935
  https://pmc.ncbi.nlm.nih.gov/articles/PMC8936487/

• Zyla J, Marczyk M, Weiner J, Polanska J. Ranking metrics in gene set enrichment analysis: do they matter?. BMC Bioinformatics. 2017;18(1):256. Published 2017 May 12. doi:10.1186/s12859-017-1674-0 https://pubmed.ncbi.nlm.nih.gov/28499413/

• Topology Pathway Analyses

  • Tarca AL, Draghici S, Khatri P, et al. A novel signaling pathway impact analysis. Bioinformatics. 2009;25(1):75-82. doi:10.1093/bioinformatics/btn577
    https://pubmed.ncbi.nlm.nih.gov/18990722/
  • Nguyen T, Mitrea C, Draghici S. Network-Based Approaches for Pathway Level Analysis. Curr Protoc Bioinformatics. 2018;61(1):8.25.1-8.25.24.
    doi:10.1002/cpbi.42
    https://pubmed.ncbi.nlm.nih.gov/30040185/
  • Ma J, Shojaie A, Michailidis G. A comparative study of topology-based pathway enrichment analysis methods. BMC Bioinformatics. 2019;20(1):546. Published 2019 Nov 4. doi:10.1186/s12859-019-3146-1 https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3146-1
  • Ihnatova I, Popovici V, Budinska E. A critical comparison of topology-based pathway analysis methods. PLoS One. 2018;13(1):e0191154. Published 2018 Jan
    25. doi:10.1371/journal.pone.0191154.
        https://pubmed.ncbi.nlm.nih.gov/29370226/

Biological Knowledge Bases

• Gene Ontology (GO)
  • https://geneontology.org/docs/ontology-documentation/
  • https://geneontology.org/stats.html
  • du Plessis L, Skunca N, Dessimoz C. The what, where, how and why of gene ontology–a primer for bioinformaticians. Brief Bioinform. 2011;12(6):723-735. doi:10.1093/bib/bbr002 https://pmc.ncbi.nlm.nih.gov/articles/PMC3220872/
• KEGG
  • https://www.genome.jp/kegg/kegg1a.html
  • https://www.genome.jp/kegg/docs/statistics.html
• Reactome
  • https://reactome.org/
• MSigDB
  • https://www.gsea-msigdb.org/gsea/msigdb
  • Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1(6):417-425. doi:10.1016/j.cels.2015.12.004
    https://pmc.ncbi.nlm.nih.gov/articles/PMC4707969/

Analysis tools

• WebGestalt
  • Wang J, Vasaikar S, Shi Z, Greer M, Zhang B. WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit. Nucleic Acids Res. 2017;45(W1):W130-W137. doi:10.1093/nar/gkx356 https://pubmed.ncbi.nlm.nih.gov/28472511/
  • Elizarraras JM, Liao Y, Shi Z, Zhu Q, Pico AR, Zhang B. WebGestalt 2024: faster gene set analysis and new support for metabolomics and multi-omics. Nucleic Acids Res. 2024;52(W1):W415-W421. doi:10.1093/nar/gkae456 https://pubmed.ncbi.nlm.nih.gov/38808672/
• GSEA
  • Broad GSEA User Guide
• clusterProfiler
• fGSEA
• DAVID
• iPathwayGuide
• Nice for proteomic data:
  • Piano
  • String

Tutorials

• Harvard Chan Bioinformatics Core on Functional Analysis
• DIY.transcriptomics Functional enrichment analysis
• GSEA with ClusterProfiler
• ESCAPE for single-cell enrichments
• Single Cell Best Practices book chapter on Funtional Enrichments
• Enrichment visualization with enrichplot
• BiostatsSquid on Pathway Enrichment Analysis and GSEA

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