期刊
GENOMICS
卷 95, 期 3, 页码 138-142出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygeno.2010.01.003
关键词
Microarray; Quality; Outlier
资金
- EU [LSHG-CT-2006-037686]
Microarrays have become a routine tool for biomedical research. Data quality assessment is an essential part of the analysis, but it is still not easy to perform objectively or in an automated manner, and as a result it is often neglected. Here, we compared two strategies of array-level quality control using five publicly available microarray experiments: outlier removal and array weights. We also compared them against no outlier removal and random array removal. We find that removing outlier arrays can improve the signal-to-noise ratio and thus strengthen the power of detecting differentially expressed genes. Using array weights is similarly effective, but its applicability is more limited. The quality metrics presented here are implemented in the Bioconductor package array Quality Metrics. (C) 2010 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据