Empirical evaluation of consistency and accuracy of methods to detect differentially expressed genes based on microarray data.

ABSTRACT:

Background

In this study, we empirically evaluated the consistency and accuracy of five different methods to detect differentially expressed genes (DEGs) based on microarray data.

Methods

Five different methods were compared, including the t-test, significance analysis of microarrays (SAM), the empirical Bayes t-test (eBayes), t-tests relative to a threshold (TREAT), and assumption adequacy averaging (AAA). The percentage of overlapping genes (POG) and the percentage of overlapping genes related (POGR) scores were used to rank the different methods on their ability to maintain a consistent list of DEGs both within the same data set and across two different data sets concerning the same disease. The power of each method was evaluated based on a simulation approach which mimic

SUBMITTER: Yang D 

PROVIDER: S-EPMC3993975 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature