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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
Bence M. Kotis
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
Stephane E. Castel
2Department of Systems Biology, Columbia University, New York, NY, USA
3New York Genome Center, New York, NY, USA
Eric J. Song
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
Nicholas Mancuso
4Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, USC, CA, USA
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.

- Supplementary materials[supplements/478116_file03.pdf]
- Supplementary Tables[supplements/478116_file04.xlsx]
Posted January 28, 2022.
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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