SMASH, a fragmentation and sequencing method for genomic copy number analysis

Wang, Z., Andrews, P., Kendall, J., Ma, B., Hakker, I., Rodgers, L., Ronemus, M., Wigler, M., Levy, D. (June 2016) SMASH, a fragmentation and sequencing method for genomic copy number analysis. Genome Res, 26 (6). pp. 844-51. ISSN 1549-5469 (Electronic)1088-9051 (Linking) (Public Dataset)

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URL: http://www.ncbi.nlm.nih.gov/pubmed/27197213
DOI: 10.1101/gr.201491.115

Abstract

Copy number variants (CNVs) underlie a significant amount of genetic diversity and disease. CNVs can be detected by a number of means, including chromosomal microarray analysis (CMA) and whole-genome sequencing (WGS), but these approaches suffer from either limited resolution (CMA) or are highly expensive for routine screening (both CMA and WGS). As an alternative, we have developed a next-generation sequencing-based method for CNV analysis termed SMASH, for short multiply aggregated sequence homologies. SMASH utilizes random fragmentation of input genomic DNA to create chimeric sequence reads, from which multiple mappable tags can be parsed using maximal almost-unique matches (MAMs). The SMASH tags are then binned and segmented, generating a profile of genomic copy number at the desired resolution. Because fewer reads are necessary relative to WGS to give accurate CNV data, SMASH libraries can be highly multiplexed, allowing large numbers of individuals to be analyzed at low cost. Increased genomic resolution can be achieved by sequencing to higher depth.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > copy number variants
Investigative techniques and equipment > assays > whole genome sequencing
CSHL Authors:
Communities: CSHL Cancer Center Program > Cancer Genetics
CSHL labs > Levy lab
CSHL labs > Wigler lab
CSHL Cancer Center Program > Cancer Genetics and Genomics Program
Depositing User: Matt Covey
Date: June 2016
Date Deposited: 24 May 2016 19:34
Last Modified: 05 Nov 2020 21:40
PMCID: PMC4889966
Related URLs:
Dataset ID:
URI: https://repository.cshl.edu/id/eprint/32806

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