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Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions

Sarah M. Urbut, Gao Wang, Peter Carbonetto, Matthew Stephens
doi: https://doi.org/10.1101/096552
Sarah M. Urbut
1Pritzker School of Medicine, Growth & Development Training Program, University of Chicago, Chicago, IL, USA.
2Department of Human Genetics, University of Chicago, Chicago, IL, USA.
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Gao Wang
2Department of Human Genetics, University of Chicago, Chicago, IL, USA.
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Peter Carbonetto
2Department of Human Genetics, University of Chicago, Chicago, IL, USA.
4Research Computing Center, University of Chicago, Chicago, IL, USA.
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Matthew Stephens
2Department of Human Genetics, University of Chicago, Chicago, IL, USA.
3Department of Statistics, University of Chicago, Chicago, IL, USA.
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Posted September 21, 2018.
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Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions
Sarah M. Urbut, Gao Wang, Peter Carbonetto, Matthew Stephens
bioRxiv 096552; doi: https://doi.org/10.1101/096552
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Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions
Sarah M. Urbut, Gao Wang, Peter Carbonetto, Matthew Stephens
bioRxiv 096552; doi: https://doi.org/10.1101/096552

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