Decomposition of mutational context signatures using quadratic programming methods [version 1; referees: awaiting peer review]
Authors
Publication Date
2016-06-07Journal Title
F1000Research
ISSN
2046-1402
Publisher
F1000Research
Volume
5
Number
1253
Language
English
Type
Article
This Version
VoR
Metadata
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Lynch, A. (2016). Decomposition of mutational context signatures using quadratic programming methods [version 1; referees: awaiting peer review]. F1000Research, 5 (1253)https://doi.org/10.12688/f1000research.8918.1
Abstract
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.
Sponsorship
AGL was supported in this work by a Cancer Research UK programme grant [C14303/A20406] to Simon Tavaré. AGL 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.
Embargo Lift Date
2100-01-01
Identifiers
External DOI: https://doi.org/10.12688/f1000research.8918.1
This record's URL: https://www.repository.cam.ac.uk/handle/1810/257266
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