Journal
NATURE PROTOCOLS
Volume 13, Issue 6, Pages 1488-1501Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/nprot.2018.033
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Funding
- DFG
- German Cancer Aid (Deutsche Krebshilfe) [109679]
- German Ministry of Science and Education (BMBF), e:Med program [01ZX1303A, 01ZX1406]
- Deutsche Forschungsgemeinschaft [CRU-286, CP2]
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The genomes of cancer cells constantly change during pathogenesis. This evolutionary process can lead to the emergence of drug-resistant mutations in subclonal populations, which can hinder therapeutic intervention in patients. Data derived from massively parallel sequencing can be used to infer these subclonal populations using tumor-specific point mutations. The accurate determination of copy-number changes and tumor impurity is necessary to reliably infer subclonal populations by mutational clustering. This protocol describes how to use Sclust, a copy-number analysis method with a recently developed mutational clustering approach. In a series of simulations and comparisons with alternative methods, we have previously shown that Sclust accurately determines copy-number states and subclonal populations. Performance tests show that the method is computationally efficient, with copy-number analysis and mutational clustering taking < 10 min. Sclust is designed such that even non-experts in computational biology or bioinformatics with basic knowledge of the Linux/Unix command-line syntax should be able to carry out analyses of subclonal populations.
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