Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype

Vinicius Tragante (Lead / Corresponding author), Johannes M. I. H. Gho, Janine F. Felix, Ramachandran S. Vasan, Nicholas L. Smith, Benjamin F. Voight, Colin Palmer, Pim van der Harst, Jason H. Moore, Folkert W. Asselbergs, CHARGE Heart Failure Working Group

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Abstract

Background: Genetic studies for complex diseases have predominantly discoveredmain effects at individual loci, but have not focused on genomic and environmentalcontexts important for a phenotype. Gene Set Enrichment Analysis (GSEA) aims toaddress this by identifying sets of genes or biological pathways contributing to aphenotype, through gene-gene interactions or other mechanisms, which are not thefocus of conventional association methods.
Results: Approaches that utilize GSEA can now take input from array chips, eithergene-centric or genome-wide, but are highly sensitive to study design, SNP selectionand pruning strategies, SNP-to-gene mapping, and pathway definitions. Here, wepresent lessons learned from our experience with GSEA of heart failure, a particularlychallenging phenotype due to its underlying heterogeneous etiology.
Conclusions: This case study shows that proper data handling is essential to avoidfalse-positive results. Well-defined pipelines for quality control are needed to avoidreporting spurious results using GSEA.
Original languageEnglish
Article number18
Pages (from-to)1-11
Number of pages11
JournalBioData Mining
Volume10
DOIs
Publication statusPublished - 26 May 2017

Keywords

  • Gene set enrichment analyses
  • Heart failure
  • Coronary artery disease

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    Tragante, V., Gho, J. M. I. H., Felix, J. F., Vasan, R. S., Smith, N. L., Voight, B. F., Palmer, C., van der Harst, P., Moore, J. H., Asselbergs, F. W., & CHARGE Heart Failure Working Group (2017). Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype. BioData Mining, 10, 1-11. [18]. https://doi.org/10.1186/s13040-017-0137-5