التفاصيل البيبلوغرافية
| العنوان: |
Gene set enrichment analysis made simple. |
| المؤلفون: |
Irizarry, Rafael A., Chi Wang, Yun Zhou, Speed, Terence P. |
| المصدر: |
Statistical Methods in Medical Research; Dec2009, Vol. 18 Issue 6, p565-575, 11p, 1 Diagram, 1 Chart, 4 Graphs |
| مصطلحات موضوعية: |
GENETIC research, GENE expression, GENOMICS, MOLECULAR biology, MULTIPLE comparisons (Statistics) |
| مصطلحات جغرافية: |
AUSTRALIA |
| مستخلص: |
Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, choose an appropriate cut-off, and create a list of candidate genes. This approach has been criticised for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, the most popular method, gene set enrichment analysis (GSEA), seems overly complicated. Furthermore, GSEA is based on a statistical test known for its lack of sensitivity. In this article we compare the performance of a simple alternative to GSEA. We find that this simple solution clearly outperforms GSEA. We demonstrate this with eight different microarray datasets. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
