@article {Mulqueen157230, author = {Ryan M. Mulqueen and Dmitry Pokholok and Steve Norberg and Andrew J. Fields and Duanchen Sun and Kristof A. Torkenczy and Jay Shendure and Cole Trapnell and Brian J. O{\textquoteright}Roak and Zheng Xia and Frank J. Steemers and Andrew C. Adey}, title = {Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing}, elocation-id = {157230}, year = {2017}, doi = {10.1101/157230}, publisher = {Cold Spring Harbor Laboratory}, abstract = {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 {\textpm} 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.}, URL = {https://www.biorxiv.org/content/early/2017/06/28/157230}, eprint = {https://www.biorxiv.org/content/early/2017/06/28/157230.full.pdf}, journal = {bioRxiv} }