UGM: a more stable procedure for large-scale multiple testing problems, new solutions to identify oncogene.

ABSTRACT: Variations of gene expression levels play an important role in tumors. There are numerous methods to identify differentially expressed genes in high-throughput sequencing. Several algorithms endeavor to identify distinctive genetic patterns susceptable to particular diseases. Although these processes have been proved successful, the probability that the number of non-differentially expressed genes measured by false discovery rate (FDR) has a large standard deviation, and the misidentification rate (type I error) grows rapidly when the number of genes to be detected become larger. In this study we developed a new method, Unit Gamma Measurement (UGM), accounting for multiple hypotheses test statistics distribution, which could reduce the dependency problem. Simulated expression profile data

SUBMITTER: Liu C 

PROVIDER: S-EPMC6927121 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature