Title |
ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
|
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Published in |
Genome Biology, March 2017
|
DOI | 10.1186/s13059-017-1169-3 |
Pubmed ID | |
Authors |
Sohrab Salehi, Adi Steif, Andrew Roth, Samuel Aparicio, Alexandre Bouchard-Côté, Sohrab P. Shah |
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. |
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Geographical breakdown
Country | Count | As % |
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United States | 3 | 23% |
Canada | 2 | 15% |
United Kingdom | 2 | 15% |
Norway | 1 | 8% |
Unknown | 5 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 8 | 62% |
Members of the public | 3 | 23% |
Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Korea, Republic of | 1 | <1% |
United States | 1 | <1% |
Unknown | 110 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 26 | 23% |
Researcher | 23 | 21% |
Student > Bachelor | 12 | 11% |
Student > Master | 10 | 9% |
Student > Doctoral Student | 7 | 6% |
Other | 17 | 15% |
Unknown | 17 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 26 | 23% |
Agricultural and Biological Sciences | 22 | 20% |
Computer Science | 18 | 16% |
Engineering | 7 | 6% |
Medicine and Dentistry | 7 | 6% |
Other | 11 | 10% |
Unknown | 21 | 19% |