Expression profiling by array Third-party reanalysis
Summary
Numerous gene expression datasets from diverse human tissue samples have been already deposited in the public domain. There have been several attempts to do large scale meta-analyses of all of these datasets. Most of these analyses summarize pairwise gene expression relationships using correlation, or identify differentially expressed genes in two conditions. We propose here a new large scale meta-analysis of all of the publicly available human datasets to identify Boolean logical relationships between genes. Boolean logic is a branch of mathematics that deals with two possible values. In the context of gene expression datasets we use qualitative high and low expression values. A strong logical relationship between genes emerges if at least one of the quadrants is sparsely populated.
Overall design
25,955 published human microarray samples assayed on the GPL570 were re-analyzed. RMA was used to normalize the RAW CEL files all together.
