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Nat Methods DOI:10.1038/nmeth.1276

High-resolution mapping of copy-number alterations with massively parallel sequencing.

Publication TypeJournal Article
Year of Publication2009
AuthorsChiang, DY, Getz, G, Jaffe, DB, O'Kelly, MJT, Zhao, X, Carter, SL, Russ, C, Nusbaum, C, Meyerson, M, Lander, ES
JournalNat Methods
Date Published2009 Jan
KeywordsAlgorithms, Base Sequence, Cell Line, Tumor, Chromosomes, Human, Databases, Genetic, Gene Dosage, Humans

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).


Alternate JournalNat. Methods
PubMed ID19043412
PubMed Central IDPMC2630795
Grant ListU54 HG003067-01 / HG / NHGRI NIH HHS / United States
5U24 CA 126546 / CA / NCI NIH HHS / United States
U54 HG003067 / HG / NHGRI NIH HHS / United States
5U54 HG 00367 / HG / NHGRI NIH HHS / United States
U24 CA126546-01 / CA / NCI NIH HHS / United States
U24 CA126546 / CA / NCI NIH HHS / United States