Inference of transcriptional regulation in cancers
View/ Open
Author
Note: Order does not necessarily reflect citation order of authors.Published Version
https://doi.org/10.1073/pnas.1424272112Metadata
Show full item recordCitation
Jiang, Peng, Matthew L. Freedman, Jun S. Liu, and Xiaole Shirley Liu. 2015. “Inference of Transcriptional Regulation in Cancers.” Proc Natl Acad Sci USA 112 (25) (June 8): 7731–7736. doi:10.1073/pnas.1424272112.Abstract
We developed an efficient and accurate computational framework, RABIT (regression analysis with background integration), and comprehensively integrated public transcription factor (TF)-binding profiles with TCGA tumor-profiling datasets in 18 cancer types. To systematically search for cancer-associated TFs, RABIT controls the effect of tumor-confounding factors on transcriptional regulation, such as copy number alteration, DNA methylation, and TF somatic mutation. Our predicted TF regulatory activity in tumors is highly consistent with the knowledge from cancer gene databases and reveals many previously unidentified cancer-associated TFs. We also analyzed RNA-binding protein regulation in cancer and demonstrated that RABIT is a general platform for predicting oncogenic gene expression regulators.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4485084/Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:27002089
Collections
- SPH Scholarly Articles [6362]
Contact administrator regarding this item (to report mistakes or request changes)