Bayesian log-normal deconvolution for enhanced in silico microdissection of bulk gene expression data

Bárbara Andrade Barbosa, Saskia D. Asten, Ji Won Oh, Arantza Farina-Sarasqueta, Joanne Verheij, Frederike Dijk, Hanneke W. M. Laarhoven, Bauke Ylstra, Juan J. Garcia Vallejo, Mark A. Wiel () and Yongsoo Kim ()
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Bárbara Andrade Barbosa: Amsterdam UMC, Vrije Universiteit Amsterdam
Saskia D. Asten: Amsterdam UMC, Vrije Universiteit Amsterdam
Ji Won Oh: Kyungpook National University
Arantza Farina-Sarasqueta: Amsterdam UMC, University of Amsterdam
Joanne Verheij: Amsterdam UMC, University of Amsterdam
Frederike Dijk: Amsterdam UMC, University of Amsterdam
Hanneke W. M. Laarhoven: Amsterdam UMC, University of Amsterdam
Bauke Ylstra: Amsterdam UMC, Vrije Universiteit Amsterdam
Juan J. Garcia Vallejo: Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Infection and Immunity Institute
Mark A. Wiel: Amsterdam UMC, Vrije Universiteit Amsterdam
Yongsoo Kim: Amsterdam UMC, Vrije Universiteit Amsterdam

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: Abstract Deconvolution of bulk gene expression profiles into the cellular components is pivotal to portraying tissue’s complex cellular make-up, such as the tumor microenvironment. However, the inherently variable nature of gene expression requires a comprehensive statistical model and reliable prior knowledge of individual cell types that can be obtained from single-cell RNA sequencing. We introduce BLADE (Bayesian Log-normAl Deconvolution), a unified Bayesian framework to estimate both cellular composition and gene expression profiles for each cell type. Unlike previous comprehensive statistical approaches, BLADE can handle > 20 types of cells due to the efficient variational inference. Throughout an intensive evaluation with > 700 simulated and real datasets, BLADE demonstrated enhanced robustness against gene expression variability and better completeness than conventional methods, in particular, to reconstruct gene expression profiles of each cell type. In summary, BLADE is a powerful tool to unravel heterogeneous cellular activity in complex biological systems from standard bulk gene expression data.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26328-2

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DOI: 10.1038/s41467-021-26328-2

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