High-resolution mapping of copy-number alterations with massively parallel sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-01

AUTHORS

Derek Y Chiang, Gad Getz, David B Jaffe, Michael J T O'Kelly, Xiaojun Zhao, Scott L Carter, Carsten Russ, Chad Nusbaum, Matthew Meyerson, Eric S Lander

ABSTRACT

Cancer results from somatic alterations in key genes, including point mutations, copy-number alterations and structural rearrangements. A powerful way to discover cancer-causing genes is to identify genomic regions that show recurrent copy-number alterations (gains and losses) in tumor genomes. Recent advances in sequencing technologies suggest that massively parallel sequencing may provide a feasible alternative to DNA microarrays for detecting copy-number alterations. Here we present: (i) a statistical analysis of the power to detect copy-number alterations of a given size; (ii) SegSeq, an algorithm to segment equal copy numbers from massively parallel sequence data; and (iii) analysis of experimental data from three matched pairs of tumor and normal cell lines. We show that a collection of approximately 14 million aligned sequence reads from human cell lines has comparable power to detect events as the current generation of DNA microarrays and has over twofold better precision for localizing breakpoints (typically, to within approximately 1 kilobase). More... »

PAGES

99-103

Journal

TITLE

Nature Methods

ISSUE

1

VOLUME

6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nmeth.1276

DOI

http://dx.doi.org/10.1038/nmeth.1276

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025333243

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19043412


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