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.
- Gene set enrichment analyses
- Heart failure
- Coronary artery disease