Modeling multifunctionality of genes with secondary gene co-expression networks in human brain provides novel disease insights.
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ABSTRACT: Motivation
Co-expression networks are a powerful gene expression analysis method to study how genes co-express together in clusters with functional coherence that usually resemble specific cell type behaviour for the genes involved. They can be applied to bulk-tissue gene expression profiling and assign function, and usually cell type specificity, to a high percentage of the gene pool used to construct the network. One of the limitations of this method is that each gene is predicted to play a role in a specific set of coherent functions in a single cell type (i.e. at most we get a single Results
We applied GMSCA to 27 co-expression networks derived from bulk-tissue gene expression profiling of a variety of brain tissues. Neurons and glial cells (microglia, astrocytes and oligodendrocytes) were considered the main cell types. Applying this approach, we increase the overall number of predicted triplets Availability
The tool is available at GitHub, https://github.com/drlaguna/GMSCA as open-source software.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Sanchez JA
PROVIDER: S-EPMC8479669 | biostudies-literature |
REPOSITORIES: biostudies-literature
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