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ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data Salehi, Sohrab; Steif, Adi; Roth, Andrew J. L.; Aparicio, Samuel, 1963-; Bouchard-Côté, Alexandre; Shah, Sohrab P.

Abstract

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.

Item Metadata

Title
ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
Creator
Salehi, Sohrab; Steif, Adi; Roth, Andrew J. L.; Aparicio, Samuel, 1963-; Bouchard-Côté, Alexandre; Shah, Sohrab P.
Contributor
University of British Columbia. Graduate Program in Bioinformatics
Publisher
BioMed Central
Date Issued
2017-03-01
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.
Subject
Intra-tumour heterogeneity; Clonal evolution; Joint probabilistic model; Distance dependent; Chinese restaurant process; Single cell sequencing; Next-generation sequencing
Genre
Article
Type
Text
Language
eng
Date Available
2017-12-14
Provider
Vancouver : University of British Columbia Library
Rights
Attribution 4.0 International (CC BY 4.0)
DOI
10.14288/1.0362034
URI
http://hdl.handle.net/2429/64003
Affiliation
Medicine, Faculty of; Science, Faculty of; Other UBC; Non UBC; Pathology and Laboratory Medicine, Department of; Statistics, Department of
Citation
Genome Biology. 2017 Mar 01;18(1):44
Publisher DOI
10.1186/s13059-017-1169-3
Peer Review Status
Reviewed
Scholarly Level
Faculty
Copyright Holder
The Author(s)
Rights URI
http://creativecommons.org/licenses/by/4.0/
Aggregated Source Repository
DSpace

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Attribution 4.0 International (CC BY 4.0)