Genomic regression analysis of coordinated expression.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 29259170.
- Also identified by DOI 10.1038/s41467-017-02181-0 and PMC identifier 5736603.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Co-expression analysis is widely used to predict gene function and to identify functionally related gene sets. However, co-expression analysis using human cancer transcriptomic data is confounded by somatic copy number alterations (SCNA), which produce co-expression signatures based on physical proximity rather than biological function. To better understand gene-gene co-expression based on biological regulation but not SCNA, we describe a method termed "Genomic Regression Analysis of Coordinated Expression" (GRACE) to adjust for the effect of SCNA in co-expression analysis. The results from analyses of TCGA, CCLE, and NCI60 data sets show that GRACE can improve our understanding of how a transcriptional network is re-wired in cancer. A user-friendly web database populated with data sets from The Cancer Genome Atlas (TCGA) is provided to allow customized query.
Medical subject headings
- Databases, Nucleic Acid
- Gene Regulatory Networks
- Genomics
- Neoplasms