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Genome biologyBioinformaticsPeer-reviewed journal article

Universal chromatin state annotation of the mouse genome

Ha VuiD, Jason ErnstiD

PDFDOIPreprint

Abstract

Genome-wide chromatin states learned from integrating genome-wide maps of multiple epigenetic marks within the same cell type have been widely used to generate genome annotations of individual cell types. An alternative strategy based on stacked modeling can provide a single universal chromatin state annotation based jointly on data from many cell types. In human, such an approach was recently demonstrated and the resulting chromatin state annotation, denoted full-stack, was shown to have complementary advantages to per-cell-type annotations. However, an analogous annotation has not been previously available in mouse. Here, we produce a chromatin state annotation for mouse based on 901 datasets assaying 14 chromatin marks in 26 different cell or tissue types. To characterize each chromatin state, we relate the states to other external annotations and compare them to analogously defined states in human. We expect the full-stack chromatin state annotation for mouse will be a useful resource for studying the genome of this key mammalian model organism.

Citations
27
FWCI
2.40
Field percentile
top 10%

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Ha Vu, Jason Ernst·Genome biology·Jan 6, 2022· 130 citations