Importance of collection in gene set enrichment analysis of drug response in cancer cell lines
| Autor: | Alain R. Bateman, Nehme El-Hachem, Hugo J.W.L. Aerts, Benjamin Haibe-Kains, Andrew H. Beck |
|---|---|
| Přispěvatelé: | Promovendi ODB, Radiotherapie, RS: GROW - Oncology, RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Context (language use)
Computational biology computer.software_genre Article Set (abstract data type) Cell Line Tumor Neoplasms Databases Genetic Drug response Humans Leverage (statistics) Medicine Gene Multidisciplinary business.industry Gene Expression Profiling Gene sets Computational Biology Gene Expression Regulation Pharmaceutical Preparations Data mining Cancer cell lines business computer Algorithms Human cancer |
| Zdroj: | Scientific Reports, 4:4092. Nature Publishing Group Scientific Reports |
| ISSN: | 2045-2322 |
| Popis: | Gene set enrichment analysis (GSEA) associates gene sets and phenotypes, its use is predicated on the choice of a pre-defined collection of sets. The defacto standard implementation of GSEA provides seven collections yet there are no guidelines for the choice of collections and the impact of such choice, if any, is unknown. Here we compare each of the standard gene set collections in the context of a large dataset of drug response in human cancer cell lines. We define and test a new collection based on gene co-expression in cancer cell lines to compare the performance of the standard collections to an externally derived cell line based collection. The results show that GSEA findings vary significantly depending on the collection chosen for analysis. Henceforth, collections should be carefully selected and reported in studies that leverage GSEA. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|