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BrainGENIE: The Brain Gene Expression and Network Imputation Engine
by
Kelly, Brian
, Glatt, Stephen J
, Stamova, Boryana
, Hess, Jonathan L
, Carr, Vaughan
, de Jong, Simone
, Kong, Sek Won
, Tsuang, Ming T
, Chen, Samuel
, Tooney, Paul
, Beveridge, Natalie Jane
, Zhang, Chunling
, Gardiner, Erin
, Faraone, Stephen V
, Kumarasinghe, Nishantha
, Ophoff, Roel
, Cairns, Murray
, Scott, Rodney
, Quinn, Thomas P
, Hearn, Gentry C
, Schall, Ulrich
in
Gene expression
2023
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BrainGENIE: The Brain Gene Expression and Network Imputation Engine
by
Kelly, Brian
, Glatt, Stephen J
, Stamova, Boryana
, Hess, Jonathan L
, Carr, Vaughan
, de Jong, Simone
, Kong, Sek Won
, Tsuang, Ming T
, Chen, Samuel
, Tooney, Paul
, Beveridge, Natalie Jane
, Zhang, Chunling
, Gardiner, Erin
, Faraone, Stephen V
, Kumarasinghe, Nishantha
, Ophoff, Roel
, Cairns, Murray
, Scott, Rodney
, Quinn, Thomas P
, Hearn, Gentry C
, Schall, Ulrich
in
Gene expression
2023
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Do you wish to request the book?
BrainGENIE: The Brain Gene Expression and Network Imputation Engine
by
Kelly, Brian
, Glatt, Stephen J
, Stamova, Boryana
, Hess, Jonathan L
, Carr, Vaughan
, de Jong, Simone
, Kong, Sek Won
, Tsuang, Ming T
, Chen, Samuel
, Tooney, Paul
, Beveridge, Natalie Jane
, Zhang, Chunling
, Gardiner, Erin
, Faraone, Stephen V
, Kumarasinghe, Nishantha
, Ophoff, Roel
, Cairns, Murray
, Scott, Rodney
, Quinn, Thomas P
, Hearn, Gentry C
, Schall, Ulrich
in
Gene expression
2023
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BrainGENIE: The Brain Gene Expression and Network Imputation Engine
Journal Article
BrainGENIE: The Brain Gene Expression and Network Imputation Engine
2023
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Overview
In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood–brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947–11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues.
Publisher
Nature Publishing Group
Subject
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