henhaobio
Sign in

Genome biologyBioinformaticsPeer-reviewed journal article

Cross-species and tissue imputation of species-level DNA methylation samples across mammalian species.

Emily Maciejewski, Steve HorvathiD, Jason ErnstiD

PDFDOIPreprint

Abstract

DNA methylation data offers valuable insights into various aspects of mammalian biology. The recent introduction and large-scale application of the mammalian methylation array has significantly expanded the availability of such data across conserved sites in many mammalian species. In our study, we consider 13,245 samples profiled on this array encompassing 348 species and 59 tissues from 746 species-tissue combinations. While having some coverage of many different species and tissue types, this data captures only 3.6% of potential species-tissue combinations. To address this gap, we developed CMImpute (Cross-species Methylation Imputation), a method based on a Conditional Variational Autoencoder, to impute DNA methylation for non-profiled species-tissue combinations. In cross-validation, we demonstrate that CMImpute achieves a strong correlation with actual observed values, surpassing several baseline methods. Using CMImpute we imputed methylation data for 19,786 new species-tissue combinations. We believe that both CMImpute and our imputed data resource will be useful for DNA methylation analyses across a wide range of mammalian species.

Citations
6
FWCI
1.20
Field percentile
top 24%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISArneson '22Pham '26Duplan '25Li '20Moghul '25Tang '25
65% semantic matchBioinformatics
A Arneson, Amin Haghani, Michael James Thompson+15 more·Nature Communications·Feb 10, 2022· 234 citations