4.6 Article

Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)

期刊

PLOS COMPUTATIONAL BIOLOGY
卷 15, 期 4, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1006899

关键词

-

资金

  1. National Institutes of Science (NIH) [U19AI117873]
  2. United States-Israel Binational Science Foundation [2013395]

向作者/读者索取更多资源

Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another approach to increase the power to detect biologically relevant changes by integrating information from multiple studies. Here, we present a framework that combines both approaches and allows for meta-analysis of gene sets. QuSAGE meta-analysis extends our previously published QuSAGE framework, which offers several advantages for gene set analysis, including fully accounting for gene-gene correlations and quantifying gene set activity as a full probability density function. Application of QuSAGE meta-analysis to influenza vaccination response shows it can detect significant activity that is not apparent in individual studies.

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。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据