Year: 2015
Type: article
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.
Source: Genome biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,490
Funders: Damon Runyon Cancer Research Foundation, Cancer Prevention and Research Institute of Texas, Robert J. Kleberg, Jr. and Helen C. Kleberg Foundation, National Institutes of Health, University of Texas MD Anderson Cancer Center, National Cancer Institute, Moonshot Research and Development Program
Awards: G111615301, G1468253849, G1901027039, The Future of Cancer Research: Training Program for Basic and Translational Scientists, G5223222499, G6011371529, G625906225, Developing a whole-genome sequencing method for single human cells, G6736661663, G7404538191, G788993117, Cancer Center Support Grant
OpenAlex ID: W2080309308