Coexpression analysis of human genes across many microarray data sets.

@article{citeulike:835519, abstract = {We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function.}, address = {Columbia Genome Center, Columbia University, New York, New York 10032, USA.}, author = {Lee, H. K. and Hsu, A. K. and Sajdak, J. and Qin, J. and Pavlidis, P. }, citeulike-article-id = {835519}, doi = {10.1101/gr.1910904}, issn = {1088-9051}, journal = {Genome Res}, keywords = {data-integration, gene-expression, systems-biology}, month = {June}, number = {6}, pages = {1085--1094}, posted-at = {2008-05-09 16:37:35}, priority = {2}, title = {Coexpression analysis of human genes across many microarray data sets.}, url = {http://dx.doi.org/10.1101/gr.1910904}, volume = {14}, year = {2004} }

TY - JOUR ID - citeulike:835519 TI - Coexpression analysis of human genes across many microarray data sets. JF - Genome Res VL - 14 IS - 6 SP - 1085 EP - 1094 AD - Columbia Genome Center, Columbia University, New York, New York 10032, USA. SN - 1088-9051 N2 - We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function. KW - data-integration KW - gene-expression KW - systems-biology AU - Lee, HK AU - Hsu, AK AU - Sajdak, J AU - Qin, J AU - Pavlidis, P PY - 2004/06// UR - http://dx.doi.org/10.1101/gr.1910904 ER -