RT Journal Article SR Electronic T1 Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing JF bioRxiv FD Cold Spring Harbor Laboratory SP 157230 DO 10.1101/157230 A1 Ryan M. Mulqueen A1 Dmitry Pokholok A1 Steve Norberg A1 Andrew J. Fields A1 Duanchen Sun A1 Kristof A. Torkenczy A1 Jay Shendure A1 Cole Trapnell A1 Brian J. O’Roak A1 Zheng Xia A1 Frank J. Steemers A1 Andrew C. Adey YR 2017 UL http://biorxiv.org/content/early/2017/06/28/157230.abstract AB Here we present a novel method: single-cell combinatorial indexing for methylation analysis (sci-MET), which is the first highly scalable assay for whole genome methylation profiling of single cells. We use sci-MET to produce 2,697 total single-cell bisulfite sequencing libraries and achieve read alignment rates of 69 ± 7%, comparable to those of bulk cell methods. As a proof of concept, we applied sci-MET to successfully deconvolve the cellular identity of a mixture of three human cell lines.