Large-scale epigenome imputation improves data quality and disease variant enrichment

With hundreds of epigenomic maps, the opportunity arises to exploit the correlated nature of epigenetic signals, across both marks and samples, for large-scale prediction of additional datasets. Here, we undertake epigenome imputation by leveraging such correlations through an ensemble of regression trees. We impute 4,315 high-resolution signal maps, of which 26% are also experimentally observed. Imputed signal tracks show overall similarity to observed signals, and surpass experimental datasets in consistency, recovery of gene annotations, and enrichment for disease-associated variants. We use the imputed data to detect low quality experimental datasets, to find genomic sites with unexpected epigenomic signals, to define high-priority marks for new experiments, and to delineate chromatin states in 127 reference epigenomes spanning diverse tissues and cell types. Our imputed datasets provide the most comprehensive human regulatory annotation to date, and our approach and the ChromImpute software constitute a useful complement to large-scale experimental mapping of epigenomic information. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms Correspondences should be addressed to J.E. ([email protected]) or M.K. ([email protected]). Author Contributions J.E. and M.K. developed the method, analyzed the results, and wrote the paper. Competing Financial Interests The authors declare no competing financial interests. Availability of Imputed Signal Data, Imputation based Peak Calls and Chromatin States, and ChromImpute software All imputed signal datasets and peak calls and chromatin states based on imputed data are available from http://compbio.mit.edu/ roadmap. The ChromImpute software is available at http://www.biolchem.ucla.edu/labs/ernst/ChromImpute and source code is maintained at https://github.com/ernstlab/ChromImpute. HHS Public Access Author manuscript Nat Biotechnol. Author manuscript; available in PMC 2015 October 01. Published in final edited form as: Nat Biotechnol. 2015 April ; 33(4): 364–376. doi:10.1038/nbt.3157. A uhor M anscript