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

被引:153
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
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
收藏
页码:1199 / 1203
页数:5
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