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      Bayesian method to predict individual SNP genotypes from gene expression data.

      1 , ,
      Nature genetics
      Springer Science and Business Media LLC

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          Abstract

          RNA profiling can be used to capture the expression patterns of many genes that are associated with expression quantitative trait loci (eQTLs). Employing published putative cis eQTLs, we developed a Bayesian approach to predict SNP genotypes that is based only on RNA expression data. We show that predicted genotypes can accurately and uniquely identify individuals in large populations. When inferring genotypes from an expression data set using eQTLs of the same tissue type (but from an independent cohort), we were able to resolve 99% of the identities of individuals in the cohort at P(adjusted) ≤ 1 × 10(-5). When eQTLs derived from one tissue were used to predict genotypes using expression data from a different tissue, the identities of 90% of the study subjects could be resolved at P(adjusted) ≤ 1 × 10(-5). We discuss the implications of deriving genotypic information from RNA data deposited in the public domain.

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          Author and article information

          Journal
          Nat Genet
          Nature genetics
          Springer Science and Business Media LLC
          1546-1718
          1061-4036
          May 2012
          : 44
          : 5
          Affiliations
          [1 ] Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York, USA. eric.schadt@mssm.edu
          Article
          ng.2248
          10.1038/ng.2248
          22484626
          ad74191b-9093-4856-b0c4-e7b73de6709a
          History

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