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- Title
Empirical null distribution based modeling of multi-class differential gene expression detection.
- Authors
Cao, Xiting; Wu, Baolin; Hertz, Marshall I
- Abstract
In this paper, we study the multi-class differential gene expression detection for microarray data. We propose a likelihood based approach to estimating an empirical null distribution to incorporate gene interactions and provide more accurate false positive control than the commonly used permutation or theoretical null distribution based approach. We propose to rank important genes by p-values or local false discovery rate based on the estimated empirical null distribution. Through simulations and application to a lung transplant microarray data, we illustrate the competitive performance of the proposed method.
- Publication
Journal of applied statistics, 2013, Vol 40, Issue 2, p347
- ISSN
0266-4763
- Publication type
Journal Article
- DOI
10.1080/02664763.2012.743976