PREDICTD PaRallel Epigenomics Data Imputation with Cloud-based Tensor Decomposition

Timothy J. Durham; Maxwell W. Libbrecht; J. Jeffry Howbert; Jeff Bilmes; William Stafford Noble

doi:10.1038/s41467-018-03635-9

Nature Communications (Apr 2018)

PREDICTD PaRallel Epigenomics Data Imputation with Cloud-based Tensor Decomposition

Timothy J. Durham,
Maxwell W. Libbrecht,
J. Jeffry Howbert,
Jeff Bilmes,
William Stafford Noble

Affiliations

Timothy J. Durham: Department of Genome Sciences, University of Washington
Maxwell W. Libbrecht: Department of Genome Sciences, University of Washington
J. Jeffry Howbert: Department of Genome Sciences, University of Washington
Jeff Bilmes: Department of Electrical Engineering, University of Washington
William Stafford Noble: Department of Genome Sciences, University of Washington

DOI: https://doi.org/10.1038/s41467-018-03635-9
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 15

Abstract

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Assays to characterize the epigenome and interrogate chromatin state genome wide have so far been performed in a selected set of conditions. Here, Durham et al. develop a computational method based on tensor decomposition to impute missing experiments in collections of epigenomics experiments.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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