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Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data

Nava Ehsan, Bence M. Kotis, Stephane E. Castel, Eric J. Song, Nicholas Mancuso, Pejman Mohammadi
doi: https://doi.org/10.1101/2022.01.28.478116
Nava Ehsan
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
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Bence M. Kotis
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
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Stephane E. Castel
2Department of Systems Biology, Columbia University, New York, NY, USA
3New York Genome Center, New York, NY, USA
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Eric J. Song
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
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Nicholas Mancuso
4Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, USC, CA, USA
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Pejman Mohammadi
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
5Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, CA, USA.
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  • For correspondence: pejman@scripps.edu
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Posted January 28, 2022.
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Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data
Nava Ehsan, Bence M. Kotis, Stephane E. Castel, Eric J. Song, Nicholas Mancuso, Pejman Mohammadi
bioRxiv 2022.01.28.478116; doi: https://doi.org/10.1101/2022.01.28.478116
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Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data
Nava Ehsan, Bence M. Kotis, Stephane E. Castel, Eric J. Song, Nicholas Mancuso, Pejman Mohammadi
bioRxiv 2022.01.28.478116; doi: https://doi.org/10.1101/2022.01.28.478116

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