Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 102, Issue 36, Pages 12837-12842Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0504609102
Keywords
aging; differential expression; expression arrays; Q values; time series
Categories
Funding
- NHGRI NIH HHS [R01 HG002913, R01 HG002913-01] Funding Source: Medline
- NIGMS NIH HHS [U54 GM2119-03, U54 GM062119] Funding Source: Medline
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Characterizing the genome-wide dynamic regulation of gene expression is important and will be of much interest in the future. However, there is currently no established method for identifying differentially expressed genes in a time course study. Here we propose a significance method for analyzing time course microarray studies that can be applied to the typical types of comparisons and sampling schemes. This method is applied to two studies on humans. In one study, genes are identified that show differential expression over time in response to in vivo endotoxin administration. By using our method, 7,409 genes are called significant at a 1% false-discovery rate level, whereas several existing approaches fail to identify any genes. In another study, 417 genes are identified at a 10% false-discovery rate level that show expression changing with age in the kidney cortex. Here it is also shown that as many as 47% of the genes change with age in a manner more complex than simple exponential growth or decay. The methodology proposed here has been implemented in the freely distributed and open-source EDGE software package.
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