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Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
2013 (engelsk)Inngår i: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, nr 3, s. R24-Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Whole-genome sequencing of tumor tissue has the potential to provide comprehensive characterization of genomic alterations in tumor samples. We present Patchwork, a new bioinformatic tool for allele-specific copy number analysis using whole-genome sequencing data. Patchwork can be used to determine the copy number of homologous sequences throughout the genome, even in aneuploid samples with moderate sequence coverage and tumor cell content. No prior knowledge of average ploidy or tumor cell content is required. Patchwork is freely available as an R package, installable via R-Forge (http://patchwork.r-forge.r-project.org/).

sted, utgiver, år, opplag, sider
2013. Vol. 14, nr 3, s. R24-
Emneord [en]
Cancer, allele-specific copy number analysis, whole-genome sequencing, aneuploidy, tumor heterogeneity, chromothripsis
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-215306DOI: 10.1186/gb-2013-14-3-r24ISI: 000328193700004OAI: oai:DiVA.org:uu-215306DiVA, id: diva2:686747
Tilgjengelig fra: 2014-01-13 Laget: 2014-01-13 Sist oppdatert: 2017-12-06bibliografisk kontrollert
Inngår i avhandling
1. Copy Number Analysis of Cancer
Åpne denne publikasjonen i ny fane eller vindu >>Copy Number Analysis of Cancer
2015 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

By accurately describing cancer genomes, we may link genomic mutations to phenotypic effects and eventually treat cancer patients based on the molecular cause of their disease, rather than generalizing treatment based on cell morphology or tissue of origin.

Alteration of DNA copy number is a driving mutational process in the formation and progression of cancer. Deletions and amplifications of specific chromosomal regions are important for cancer diagnosis and prognosis, and copy number analysis has become standard practice for many clinicians and researchers. In this thesis we describe the development of two computational methods, TAPS and Patchwork, for analysis of genome-wide absolute allele-specific copy number per cell in tumour samples. TAPS is used with SNP microarray data and Patchwork with whole genome sequencing data. Both are suitable for unknown average ploidy of the tumour cells, are robust to admixture of genetically normal cells, and may be used to detect genetic heterogeneity in the tumour cell population. We also present two studies where TAPS was used to find copy number alterations associated with risk of recurrence after surgery, in ovarian cancer and colon cancer. We discuss the potential of such prognostic markers and the use of allele-specific copy number analysis in research and diagnostics.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2015. s. 42
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1072
Emneord
chromosomes, oncology, bioinformatics
HSV kategori
Forskningsprogram
Bioinformatik; Onkologi; Klinisk genetik
Identifikatorer
urn:nbn:se:uu:diva-244361 (URN)978-91-554-9175-8 (ISBN)
Disputas
2015-04-17, BMC E10:1307-1309, BMC, Husargatan 3, Uppsala, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2015-03-26 Laget: 2015-02-16 Sist oppdatert: 2018-01-11

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Mayrhofer, MarkusDiLorenzo, SebastianIsaksson, Anders

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