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Since EEM assumes that module genes, i.e., genes belonging to the same expression module, behave similarly across all samples, EEM potentially fails to identify an expression module whose module genes exhibit coherent expression patterns over only a subset of samples, i.e., sample subgroup-specific expression module.
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These microRNAs exhibit a coherent expression pattern (Additional file 1, Figure S16) and are localized on chromosome 14p.
Clusters of genes with coherent expression patterns in cultured cells and in the breast tumors samples could be related to specific features of biological variation among the samples.
This reflects that coherent expression patterns indicate modular arrangements when co-expression is appropriately modeled.
We therefore compiled a collection of neuronal gene expression data to find biclusters that show coherent expression patterns over a subset of relevant samples.
We utilized a biclustering technique (ISA) to find genes with coherent expression patterns in the hippocampus, striatum and amygdala of adult wild type mice.
In each comodule, mRNAs and miRNAs exhibit coherent expression across the same samples.
Figure 3a shows the coherent expression patterns of subnetwork genes from the diseases in the subnetwork.
Conclusion: Our method produces clusters with more consistent functional annotations and more coherent expression patterns than existing clustering techniques.
These coherent expression patterns strongly suggest a functional role related to immune response, and the annotation of the genes in question bear this interpretation out.
Identified gene sets, termed contextual gene sets, have coherent expression patterns specific for a subset of samples where they have statistically significant coherency.
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