A phylogenetic latent feature model for clonal deconvolution

Marass, F., Mouliere, F., Yuan, K. , Rosenfeld, N. and Markowetz, F. (2016) A phylogenetic latent feature model for clonal deconvolution. Annals of Applied Statistics, 10(4), pp. 2377-2404. (doi: 10.1214/16-AOAS986)

[img]
Preview
Text
133959.pdf - Accepted Version

969kB

Publisher's URL: http://projecteuclid.org/euclid.aoas/1483606864

Abstract

Tumours develop in an evolutionary process, in which the accumulation of mutations produces subpopulations of cells with distinct mutational profiles, called clones. This process leads to the genetic heterogeneity widely observed in tumour sequencing data, but identifying the genotypes and frequencies of the different clones is still a major challenge. Here, we present Cloe, a phylogenetic latent feature model to deconvolute tumour sequencing data into a set of related genotypes. Our approach extends latent feature models by placing the features as nodes in a latent tree. The resulting model can capture both the acquisition and the loss of mutations, as well as episodes of convergent evolution. We establish the validity of Cloe on synthetic data and assess its performance on controlled biological data, comparing our reconstructions to those of several published state-of-the-art methods. We show that our method provides highly accurate reconstructions and identifies the number of clones, their genotypes and frequencies even at a modest sequencing depth. As a proof of concept, we apply our model to clinical data from three cases with chronic lymphocytic leukaemia and one case with acute myeloid leukaemia.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Yuan, Dr Ke
Authors: Marass, F., Mouliere, F., Yuan, K., Rosenfeld, N., and Markowetz, F.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Annals of Applied Statistics
Publisher:Institute of Mathematical Statistics
ISSN:1932-6157
ISSN (Online):1941-7330
Copyright Holders:Copyright © 2016 Institute of Mathematical Statistics
First Published:First published in Annals of Applied Statistics 10(4):2377-2404
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

University Staff: Request a correction | Enlighten Editors: Update this record