
LINK . SPRINGER . COM {
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Title:
SNES: single nucleus exome sequencing | Genome Biology
Description:
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.
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Keywords {π}
cells, single, coverage, sequencing, pubmed, data, singlecell, article, cell, exome, scholar, figure, google, genome, cas, dna, wga, nuclei, depth, detection, errors, additional, file, snes, error, dropout, central, allelic, analysis, rates, amplification, human, sites, variant, snvs, methods, capture, reference, population, technical, indels, qpcr, performed, sample, reads, calculated, files, variants, breadth, quality,
Topics {βοΈ}
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mainEntity:
headline:SNES: single nucleus exome sequencing
description: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.
datePublished:2015-03-25T00:00:00Z
dateModified:2015-03-25T00:00:00Z
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license:http://creativecommons.org/licenses/by/4.0/
sameAs:https://doi.org/10.1186/s13059-015-0616-2
keywords:
Coverage Depth
Allelic Dropout
Coverage Uniformity
Exome Capture
Exome Sequencing Data
Animal Genetics and Genomics
Human Genetics
Plant Genetics and Genomics
Microbial Genetics and Genomics
Bioinformatics
Evolutionary Biology
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ScholarlyArticle:
headline:SNES: single nucleus exome sequencing
description: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.
datePublished:2015-03-25T00:00:00Z
dateModified:2015-03-25T00:00:00Z
pageStart:1
pageEnd:10
license:http://creativecommons.org/licenses/by/4.0/
sameAs:https://doi.org/10.1186/s13059-015-0616-2
keywords:
Coverage Depth
Allelic Dropout
Coverage Uniformity
Exome Capture
Exome Sequencing Data
Animal Genetics and Genomics
Human Genetics
Plant Genetics and Genomics
Microbial Genetics and Genomics
Bioinformatics
Evolutionary Biology
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