title: Apparently low reproducibility of true differential expression discoveries in microarray studies.
abstract: BACKGROUND
  Differentially expressed gene (DEG) lists detected from different microarray studies for a same disease are often highly inconsistent. Even in technical replicate tests using identical samples, DEG detection still shows very low reproducibility. It is often believed that current small microarray studies will largely introduce false discoveries.
  
  
  RESULTS
  Based on a statistical model, we show that even in technical replicate tests using identical samples, it is highly likely that the selected DEG lists will be very inconsistent in the presence of small measurement variations. Therefore, the apparently low reproducibility of DEG detection from current technical replicate tests does not indicate low quality of microarray technology. We also demonstrate that heterogeneous biological variations existing in real cancer data will further reduce the overall reproducibility of DEG detection. Nevertheless, in small subsamples from both simulated and real data, the actual false discovery rate (FDR) for each DEG list tends to be low, suggesting that each separately determined list may comprise mostly true DEGs. Rather than simply counting the overlaps of the discovery lists from different studies for a complex disease, novel metrics are needed for evaluating the reproducibility of discoveries characterized with correlated molecular changes. Supplementaty information: Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.
authors.forename: Min
authors.initials: M
authors.lastname: Zhang
authors.forename: Chen
authors.initials: C
authors.lastname: Yao
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
authors.forename: Jinfeng
authors.initials: J
authors.lastname: Zou
authors.forename: Lin
authors.initials: L
authors.lastname: Zhang
authors.forename: Hui
authors.initials: H
authors.lastname: Xiao
authors.forename: Dong
authors.initials: D
authors.lastname: Wang
authors.forename: Da
authors.initials: D
authors.lastname: Yang
authors.forename: Xue
authors.initials: X
authors.lastname: Gong
authors.forename: Jing
authors.initials: J
authors.lastname: Zhu
authors.forename: Yanhui
authors.initials: Y
authors.lastname: Li
authors.forename: Xia
authors.initials: X
authors.lastname: Li
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015203:Reproducibility of Results