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BEDwARS: a robust Bayesian approach to bulk gene expression deconvolution with noisy reference signatures. | LitMetric

BEDwARS: a robust Bayesian approach to bulk gene expression deconvolution with noisy reference signatures.

Genome Biol

Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, Georgia Institute of Technology, 3108 U.A. Whitaker Bldg., 313 Ferst Drive, Atlanta, GA, 30332, USA.

Published: August 2023

AI Article Synopsis

Article Abstract

Differential gene expression in bulk transcriptomics data can reflect change of transcript abundance within a cell type and/or change in the proportions of cell types. Expression deconvolution methods can help differentiate these scenarios. BEDwARS is a Bayesian deconvolution method designed to address differences between reference signatures of cell types and corresponding true signatures underlying bulk transcriptomic profiles. BEDwARS is more robust to noisy reference signatures and outperforms leading in-class methods for estimating cell type proportions and signatures. Application of BEDwARS to dihydropyridine dehydrogenase deficiency identified the possible involvement of ciliopathy and impaired translational control in the etiology of the disorder.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10399072PMC
http://dx.doi.org/10.1186/s13059-023-03007-7DOI Listing

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