Browse views: by Year, by Function, by GLF, by Subfunction, by Conference, by Journal

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Shi, Leming and Jones, Wendell and Jensen, Roderick and Harris, Stephen and Perkins, Roger and Goodsaid, Federico and Guo, Lei and Croner, Lisa and Boysen, Cecilie and Fang, Hong and Qian, Feng and Amur, Shashi and Bao, Wenjun and Barbacioru, Catalin and Bertholet, Vincent and Cao, Xiaoxi and Chu, Tzu-Ming and Collins, Patrick and Fan, Xiao-hui and Frueh, Felix and Fuscoe, James and Han, jing and Guo, Xu and Herman, Damir and Hong, Huixiao and Kawasaki, Ernest and Li, Quan-Zhen and Luo, Yuling and Ma, Yunqing and Mei, Nan and Peterson, Ron and Puri, Raj (2008) The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies. BMC Bioinformatics, 9 (Suppl ). S10. ISSN 1471-2105

Abstract

BACKGROUND:Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.RESULTS:Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan � the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent P-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on P-value ranking is an expected mathematical consequence of the high variability of the t-values; the more stringent the P-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.CONCLUSION:We recommend the use of FC-ranking plus a non-stringent P cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the P-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and P-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the P criterion balances sensitivity and specificity.

Item Type: Article
Related URLs:
Related URLs:
Date Deposited: 13 Oct 2015 13:17
Last Modified: 13 Oct 2015 13:17
URI: https://oak.novartis.com/id/eprint/201

Search

Email Alerts

Register with OAK to receive email alerts for saved searches.