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

June Luo,

Editor: Suojin Wang,

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