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SNES: single nucleus exome sequencing

Authors :
Jill Waters
Yong Wang
Nicholas Navin
Marco L. Leung
Source :
Genome Biology
Publisher :
Springer Nature

Abstract

Single-cell genome sequencing methods are challenged by poor physical coverage and high error rates, making it difficult to distinguish real biological variants from technical artifacts. To address this problem, we developed a method called SNES that combines flow-sorting of single G1/0 or G2/M nuclei, time-limited multiple-displacement-amplification, exome capture, and next-generation sequencing to generate high coverage (96%) data from single human cells. We validated our method in a fibroblast cell line, and show low allelic dropout and false-positive error rates, resulting in high detection efficiencies for single nucleotide variants (92%) and indels (85%) in single cells. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0616-2) contains supplementary material, which is available to authorized users.

Details

Language :
English
ISSN :
14656906
Volume :
16
Issue :
1
Database :
OpenAIRE
Journal :
Genome Biology
Accession number :
edsair.doi.dedup.....eea022068d0f6ba173d782e37c3467e8
Full Text :
https://doi.org/10.1186/s13059-015-0616-2