Name
Abstract | ||
|---|---|---|
This case study shows that proper data handling is essential to avoid false-positive results. Well-defined pipelines for quality control are needed to avoid reporting spurious results using GSEA. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s13040-017-0137-5 | BioData Mining |
Keywords | Field | DocType |
Coronary artery disease,Gene set enrichment analyses,Heart failure | Population,Data mining,Gene,Phenotype,Computer science,Genome-wide association study,Bioinformatics,Locus (genetics),SNP | Journal |
Volume | Issue | ISSN |
10 | 1 | 1756-0381 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vinicius Tragante | 1 | 0 | 0.68 |
| Johannes M. I. H. Gho | 2 | 0 | 0.34 |
| Janine F. Felix | 3 | 0 | 0.34 |
| Ramachandran S. Vasan | 4 | 8 | 1.25 |
| Nicholas L. Smith | 5 | 0 | 0.34 |
| Benjamin F Voight | 6 | 0 | 0.68 |
| Colin Palmer | 7 | 2 | 1.03 |
| Pim van der Harst | 8 | 0 | 0.34 |
| Jason H. Moore | 9 | 1223 | 159.43 |
| Folkert W. Asselbergs | 10 | 121 | 9.36 |