Robust Tail-sum: Two-group Cancer Outlier Differential Gene Detection

by June Luo.

Abstract: There have been discussions about detecting differentially expressed (DE) genes that are over-expressed in some but not all samples in a disease group. This has become increasingly useful in cancer studies, where oncogenes are activated in only a minority of samples. To minimize the variation of coefficient of the statistic, I propose a new statistic called robust tail-sum (RTS) to detect DE genes. In simulated examples, I compare RTS to the t-statistic, the cancer outlier profile analysis, the outlier-sum and the outlier robust t-statistic. I find RTS performs consistently as the best or second best method when the number of oncogene outliers in a disease group varies. In a real example, the new method does well in detecting differentially expressed genes.

Key Words: Cancer, COPA, Gene expression analysis, Microarray, Robust, differentially expressed, false discovery rate

Author:
June Luo, jluo@clemson.edu

Editor: Suojin Wang, sjwang@stat.tamu.edu

READING THE ARTICLE: You can read the article in portable document (.pdf) format (530713 bytes.)

NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.

This page has been accessed 1636 times since OCTOBER 11, 2009.


Return to the InterStat Home Page.