Journal article

SuperFreq: Integrated mutation detection and clonal tracking in cancer

Christoffer Flensburg, Tobias Sargeant, Alicia Oshlack, Ian J Majewski

PLOS Computational Biology | PUBLIC LIBRARY SCIENCE | Published : 2020

Abstract

Analysing multiple cancer samples from an individual patient can provide insight into the way the disease evolves. Monitoring the expansion and contraction of distinct clones helps to reveal the mutations that initiate the disease and those that drive progression. Existing approaches for clonal tracking from sequencing data typically require the user to combine multiple tools that are not purpose-built for this task. Furthermore, most methods require a matched normal (non-tumour) sample, which limits the scope of application. We developed SuperFreq, a cancer exome sequencing analysis pipeline that integrates identification of somatic single nucleotide variants (SNVs) and copy number alterati..

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Grants

Awarded by Australian National Health and Medical Research Council


Awarded by Australian National Health and Medical Research Council (Independent Research Institutes Infrastructure Support Scheme grant)


Awarded by Cancer Council Victoria


Funding Acknowledgements

This work was supported by grants from the Australian National Health and Medical Research Council (www.nhmrc.gov.au) (Project Grant to IJM 1145912; Independent Research Institutes Infrastructure Support Scheme grant 9000220), the Cancer Council Victoria (www.cancervic.org.au) (grant-in-aid to IJM 1124178), a Victorian State Government Operational Infrastructure Support (OIS) grant; a Victorian Cancer Agency fellowship (to IJM) and a Felton Bequest to IJM. We also wish to acknowledge the generous support of Mr. Malcolm Broomhead who provided philanthropic support for the research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.