4.5 Article

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

Journal

GENOME BIOLOGY
Volume 18, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s13059-017-1169-3

Keywords

Intra-tumour heterogeneity; Clonal evolution; Joint probabilistic model; Distance dependent; Chinese restaurant process; Single cell sequencing; Next-generation sequencing

Funding

  1. BC Cancer Foundation
  2. Discovery Frontiers project
  3. Natural Sciences and Engineering Research Council (NSERC)
  4. Genome Canada (GC)
  5. Canadian Institutes of Health Research (CIHR
  6. Canada Foundation for Innovation (CFI)
  7. Canadian Cancer Society Research Institute
  8. Terry Fox Research Institute
  9. Canadian Institutes for Health Research (CIHR) [245779]
  10. CIHR Foundation

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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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