Universität zu Köln

Cun, Yupeng ORCID: 0000-0002-4241-8099, Yang, Tsun-Po ORCID: 0000-0002-9077-4434, Achter, Viktor, Lang, Ulrich ORCID: 0000-0001-7166-0805 and Peifer, Martin (2018). Copy-number analysis and inference of subclonal populations in cancer genomes using Sclust. Nat. Protoc., 13 (6). S. 1488 - 1502. LONDON: NATURE PUBLISHING GROUP. ISSN 1750-2799

Full text not available from this repository.

Abstract

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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Cun, Yupeng UNSPECIFIED orcid.org/0000-0002-4241-8099 UNSPECIFIED Yang, Tsun-Po UNSPECIFIED orcid.org/0000-0002-9077-4434 UNSPECIFIED Achter, Viktor UNSPECIFIED UNSPECIFIED UNSPECIFIED Lang, Ulrich UNSPECIFIED orcid.org/0000-0001-7166-0805 UNSPECIFIED Peifer, Martin UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-185416
DOI:	10.1038/nprot.2018.033
Journal or Publication Title:	Nat. Protoc.
Volume:	13
Number:	6
Page Range:	S. 1488 - 1502
Date:	2018
Publisher:	NATURE PUBLISHING GROUP
Place of Publication:	LONDON
ISSN:	1750-2799
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Mathematics and Computer Science > Institute of Computer Science
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language CELL LUNG-CANCER; CLONAL EVOLUTION; SEQUENCE DATA; TUMORS; HETEROGENEITY; MUTATIONS; HISTORY Multiple languages Biochemical Research Methods Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/18541