Significance analysis of time course microarray experiments Export

@article{citeulike:384342, abstract = {10.1073/pnas.0504609102 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 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 software package.}, address = {Department of Biostatistics, University of Washington, Seattle, WA 98195, USA. jstorey@u.washington.edu}, author = {Storey, John D. and Xiao, Wenzhong and Leek, Jeffrey T. and Tompkins, Ronald G. and Davis, Ronald W.}, citeulike-article-id = {384342}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0504609102}, citeulike-linkout-1 = {http://www.pnas.org/content/102/36/12837.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/102/36/12837.full.pdf}, citeulike-linkout-3 = {http://www.pnas.org/cgi/content/abstract/102/36/12837}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/16141318}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=16141318}, doi = {10.1073/pnas.0504609102}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, keywords = {analysis, data, experments, microarray, time-course}, month = {September}, number = {36}, pages = {12837--12842}, posted-at = {2009-06-23 22:30:38}, priority = {2}, title = {Significance analysis of time course microarray experiments}, url = {http://dx.doi.org/10.1073/pnas.0504609102}, volume = {102}, year = {2005} }

TY - JOUR ID - citeulike:384342 L3 - citeulike-article-id:384342 N2 - 10.1073/pnas.0504609102 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 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 software package. IS - 36 JF - Proceedings of the National Academy of Sciences of the United States of America SN - 0027-8424 AD - Department of Biostatistics, University of Washington, Seattle, WA 98195, USA. jstorey@u.washington.edu EP - 12842 TI - Significance analysis of time course microarray experiments VL - 102 SP - 12837 KW - analysis KW - data KW - experments KW - microarray KW - time-course AU - Storey, John AU - Xiao, Wenzhong AU - Leek, Jeffrey AU - Tompkins, Ronald AU - Davis, Ronald PY - 2005/09/06/ UR - http://dx.doi.org/10.1073/pnas.0504609102 ER -