Decomposition of mutational context signatures using quadratic programming methods

Methods for inferring signatures of mutational contexts from large cancer sequencing data sets are invaluable for biological research, but impractical for clinical application where we require tools that decompose the context data for an individual into signatures. One such method has recently been published using an iterative linear modelling approach. A natural alternative places the problem within a quadratic programming framework and is presented here, where it is seen to offer advantages of speed and accuracy. This article is included in the gateway. RPackage Andy G. Lynch ( ) Corresponding author: [email protected] Competing interests: No competing interests were declared. Lynch AG. How to cite this article: Decomposition of mutational context signatures using quadratic programming methods [version 1; 2016, :1253 (doi: ) referees: 1 approved, 1 approved with reservations] F1000Research 5 10.12688/f1000research.8918.1 © 2016 Lynch AG. This is an open access article distributed under the terms of the , which Copyright: Creative Commons Attribution Licence permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data associated with the article are available under the terms of the (CC0 1.0 Public domain dedication). Creative Commons Zero "No rights reserved" data waiver AGL was supported in this work by a Cancer Research UK programme grant [C14303/A20406] to Simon Tavaré. AGL Grant information: acknowledges the support of the University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited. Whole-genome sequencing of oesophageal adenocarcinoma was part of the oesophageal International Cancer Genome Consortium (ICGC) project. The oesophageal ICGC project was funded through a programme and infrastructure grant to Rebecca Fitzgerald as part of the OCCAMS collaboration. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 07 Jun 2016, :1253 (doi: ) First published: 5 10.12688/f1000research.8918.1 Referee Status: