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- Title
Highly scalable generation of DNA methylation profiles in single cells.
- Authors
Mulqueen, Ryan M; Pokholok, Dmitry; Norberg, Steven J; Torkenczy, Kristof A; Fields, Andrew J; Sun, Duanchen; Sinnamon, John R; Shendure, Jay; Trapnell, Cole; O'Roak, Brian J; Xia, Zheng; Steemers, Frank J; Adey, Andrew C
- Abstract
We present a highly scalable assay for whole-genome methylation profiling of single cells. We use our approach, single-cell combinatorial indexing for methylation analysis (sci-MET), to produce 3,282 single-cell bisulfite sequencing libraries and achieve read alignment rates of 68 ± 8%. We apply sci-MET to discriminate the cellular identity of a mixture of three human cell lines and to identify excitatory and inhibitory neuronal populations from mouse cortical tissue.
- Publication
Nature Biotechnology, 2018, Vol 36, Issue 5, p428
- ISSN
1087-0156
- Publication type
Article
- DOI
10.1038/nbt.4112