A hierarchical Bayesian method identifies cell-type specific changes in gene regulatory circuits in disease by integrating single-cell and three-dimensional measurements of the genome.
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References
Kim, H. D., Shay, T., O’Shea, E. K. & Regev, A. Science 325, 429–32 (2009).
Kim-Hellmuth, S. et al. Science 369, eaaz8528 (2020).
Kreitmaier, P., Katsoula, G. & Zeggini, E. Trends Genet. 39, 46–58 (2022).
Chen, X. et al. Nat. Comput. Sci. https://doi.org/10.1038/s43588-023-00476-5 (2023)
Cao, J. et al. Science. 361, 1380–1385 (2018).
Klemm, S. L., Shipony, Z. & Greenleaf, W. J. Nat. Rev. Genet. 20, 207–220 (2019).
Schoenfelder, S. & Fraser, P. Nat. Rev. Genet. 20, 437–455 (2019).
Nagano, T. et al. Nature 502, 59–64 (2013).
Lähnemann, D. et al. Genome Biol. 21, 31 (2020).
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Przytycki, P.F. Uncovering the genetic circuits that drive diseases. Nat Comput Sci 3, 584–585 (2023). https://doi.org/10.1038/s43588-023-00475-6
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DOI: https://doi.org/10.1038/s43588-023-00475-6
