An imputed genotype resource for the laboratory mouse

被引：68

作者：

Szatkiewicz, Jin P. ^{[1
]}

Beane, Glen L. ^{[1
]}

Ding, Yueming ^{[1
]}

Hutchins, Lucie ^{[1
]}

de Villena, Fernando Pardo-Manuel ^{[2
,3
]}

Churchill, Gary A. ^{[1
]}

机构：

[1] Jackson Lab, Bar Harbor, ME 04609 USA

[2] Univ N Carolina, Dept Genet, Carolina Ctr Genome Sci, Chapel Hill, NC 27599 USA

[3] Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC 27599 USA

来源：

MAMMALIAN GENOME | 2008年 / 19卷 / 03期

关键词：

D O I：

10.1007/s00335-008-9098-9

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrated that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high-density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains.

引用

页码：199 / 208

页数：10

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