henhao
Sign in
GenomicsNature Biotechnology
Peer-reviewed journal article

Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing.

Ryan M. MulqueeniD, Dmitry Pokholok, Steven J Norberg, Kristof A. TorkenczyiD, Andrew J. FieldsiD, Duanchen SuniD, John R. SinnamoniD, Jay ShendureiD, Cole TrapnelliD, Brian J. O’RoakiD, Zheng XiaiD, Frank J. Steemers, Andrew AdeyiD

PDFDOIPreprint

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 {+/-} 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.

02 /Specification & Classification

Click any tag to browse matching papers
Citations
289
FWCI
11.38
Field percentile
top 1%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISChatterton '23Nichols '24Acharya '23Zhang '23Kremer '24Mai '23
76% semantic matchGenomics
Zac Chatterton, Praves Lamichhane, Diba Ahmadi Rastegar+5 more·Cell & Bioscience·Jan 4, 2023· 29 citations