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ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data

Next-generation sequencing (NGS) of bulk tumour tissue can identify constituent cell populations in cancers and measure their abundance. This requires computational deconvolution of allelic counts from somatic mutations, which may be incapable of fully resolving the underlying population structure....

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Autores principales: Salehi, Sohrab, Steif, Adi, Roth, Andrew, Aparicio, Samuel, Bouchard-Côté, Alexandre, Shah, Sohrab P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5333399/
https://www.ncbi.nlm.nih.gov/pubmed/28249593
http://dx.doi.org/10.1186/s13059-017-1169-3
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author Salehi, Sohrab
Steif, Adi
Roth, Andrew
Aparicio, Samuel
Bouchard-Côté, Alexandre
Shah, Sohrab P.
author_facet Salehi, Sohrab
Steif, Adi
Roth, Andrew
Aparicio, Samuel
Bouchard-Côté, Alexandre
Shah, Sohrab P.
author_sort Salehi, Sohrab
collection PubMed
description Next-generation sequencing (NGS) of bulk tumour tissue can identify constituent cell populations in cancers and measure their abundance. This requires computational deconvolution of allelic counts from somatic mutations, which may be incapable of fully resolving the underlying population structure. Single cell sequencing (SCS) is a more direct method, although its replacement of NGS is impeded by technical noise and sampling limitations. We propose ddClone, which analytically integrates NGS and SCS data, leveraging their complementary attributes through joint statistical inference. We show on real and simulated datasets that ddClone produces more accurate results than can be achieved by either method alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1169-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-53333992017-03-06 ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data Salehi, Sohrab Steif, Adi Roth, Andrew Aparicio, Samuel Bouchard-Côté, Alexandre Shah, Sohrab P. Genome Biol Method Next-generation sequencing (NGS) of bulk tumour tissue can identify constituent cell populations in cancers and measure their abundance. This requires computational deconvolution of allelic counts from somatic mutations, which may be incapable of fully resolving the underlying population structure. Single cell sequencing (SCS) is a more direct method, although its replacement of NGS is impeded by technical noise and sampling limitations. We propose ddClone, which analytically integrates NGS and SCS data, leveraging their complementary attributes through joint statistical inference. We show on real and simulated datasets that ddClone produces more accurate results than can be achieved by either method alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1169-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-01 /pmc/articles/PMC5333399/ /pubmed/28249593 http://dx.doi.org/10.1186/s13059-017-1169-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Salehi, Sohrab
Steif, Adi
Roth, Andrew
Aparicio, Samuel
Bouchard-Côté, Alexandre
Shah, Sohrab P.
ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
title ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
title_full ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
title_fullStr ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
title_full_unstemmed ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
title_short ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
title_sort ddclone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5333399/
https://www.ncbi.nlm.nih.gov/pubmed/28249593
http://dx.doi.org/10.1186/s13059-017-1169-3
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