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Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance
Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715686/ https://www.ncbi.nlm.nih.gov/pubmed/31467286 http://dx.doi.org/10.1038/s41467-019-11857-8 |
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author | Luquette, Lovelace J. Bohrson, Craig L. Sherman, Max A. Park, Peter J. |
author_facet | Luquette, Lovelace J. Bohrson, Craig L. Sherman, Max A. Park, Peter J. |
author_sort | Luquette, Lovelace J. |
collection | PubMed |
description | Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance and dropout. Here, we present a framework for statistical estimation of allele-specific amplification imbalance at any given position in single cell whole-genome sequencing data by utilizing the allele frequencies of heterozygous single nucleotide polymorphisms in the neighborhood. The resulting allelic imbalance profile is critical for determining whether the variant allele fraction of an observed mutation is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single Cell ANalysis of SNVs), substantially improves the identification of somatic variants in single cells. Our allele balance framework is broadly applicable to genotype analysis of any variant type in any data that might exhibit allelic imbalance. |
format | Online Article Text |
id | pubmed-6715686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67156862019-09-03 Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance Luquette, Lovelace J. Bohrson, Craig L. Sherman, Max A. Park, Peter J. Nat Commun Article Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance and dropout. Here, we present a framework for statistical estimation of allele-specific amplification imbalance at any given position in single cell whole-genome sequencing data by utilizing the allele frequencies of heterozygous single nucleotide polymorphisms in the neighborhood. The resulting allelic imbalance profile is critical for determining whether the variant allele fraction of an observed mutation is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single Cell ANalysis of SNVs), substantially improves the identification of somatic variants in single cells. Our allele balance framework is broadly applicable to genotype analysis of any variant type in any data that might exhibit allelic imbalance. Nature Publishing Group UK 2019-08-29 /pmc/articles/PMC6715686/ /pubmed/31467286 http://dx.doi.org/10.1038/s41467-019-11857-8 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Luquette, Lovelace J. Bohrson, Craig L. Sherman, Max A. Park, Peter J. Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance |
title | Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance |
title_full | Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance |
title_fullStr | Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance |
title_full_unstemmed | Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance |
title_short | Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance |
title_sort | identification of somatic mutations in single cell dna-seq using a spatial model of allelic imbalance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715686/ https://www.ncbi.nlm.nih.gov/pubmed/31467286 http://dx.doi.org/10.1038/s41467-019-11857-8 |
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