Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data
Abstract
The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.
Subject Area
Biostatistics
Recommended Citation
Hou, Tung-Jou, "Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data" (2009). Texas Medical Center Dissertations (via ProQuest). AAI1465785.
https://digitalcommons.library.tmc.edu/dissertations/AAI1465785