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Genome Biol. 2019 Aug 28;20(1):180. doi: 10.1186/s13059-019-1784-2.

A unified encyclopedia of human functional DNA elements through fully automated annotation of 164 human cell types.

Author information

1
School of Computing Science, Simon Fraser University, Burnaby, Canada.
2
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA.
3
Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Boston, USA.
4
Department of Electrical Engineering, University of Washington, Seattle, USA.
5
Princess Margaret Cancer Centre, Toronto, Canada.
6
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
7
Department of Computer Science, University of Toronto, Toronto, Canada.
8
Department of Genome Sciences, University of Washington, Seattle, USA. wnoble@uw.edu.
9
Department of Computer Science, University of Washington, Seattle, USA. wnoble@uw.edu.

Abstract

Semi-automated genome annotation methods such as Segway take as input a set of genome-wide measurements such as of histone modification or DNA accessibility and output an annotation of genomic activity in the target cell type. Here we present annotations of 164 human cell types using 1615 data sets. To produce these annotations, we automated the label interpretation step to produce a fully automated annotation strategy. Using these annotations, we developed a measure of the importance of each genomic position called the "conservation-associated activity score." We further combined all annotations into a single, cell type-agnostic encyclopedia that catalogs all human regulatory elements.

KEYWORDS:

Chromatin; Genomics; Machine learning

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