Systematic assessment of copy number variant detection via genome-wide SNP genotyping

被引：154

作者：

Cooper, Gregory M. ^{[1
]}

Zerr, Troy ^{[1
]}

Kidd, Jeffrey M. ^{[1
]}

Eichler, Evan E. ^{[1
,2
]}

Nickerson, Deborah A. ^{[1
]}

机构：

[1] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA

[2] Howard Hughes Med Inst, Chevy Chase, MD USA

来源：

NATURE GENETICS | 2008年 / 40卷 / 10期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1038/ng.236

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.

引用

页码：1199 / 1203

页数：5

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