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Continuous-trait probabilistic model for comparing multi-species functional genomic data

Yang Yang, Quanquan Gu, Yang Zhang, Takayo Sasaki, Julianna Crivello, Rachel J. O’Neill, David M. Gilbert, Jian Ma
doi: https://doi.org/10.1101/283093
Yang Yang
Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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Quanquan Gu
Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA
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Yang Zhang
Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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Takayo Sasaki
Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA
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Julianna Crivello
Institute for Systems Genomics, Department of Molecular & Cell Biology, University of Connecticut, Storrs, CT 06269, USA
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Rachel J. O’Neill
Institute for Systems Genomics, Department of Molecular & Cell Biology, University of Connecticut, Storrs, CT 06269, USA
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David M. Gilbert
Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA
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Jian Ma
Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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  • For correspondence: jianma@cs.cmu.edu
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Summary

A large amount of multi-species functional genomic data from high-throughput assays are becoming available to help understand the molecular mechanisms for phenotypic diversity across species. However, continuous-trait probabilistic models, which are key to such comparative analysis, remain underexplored. Here we develop a new model, called phylogenetic hidden Markov Gaussian processes (Phylo-HMGP), to simultaneously infer heterogeneous evolutionary states of functional genomic features in a genome-wide manner. Both simulation studies and real data application demonstrate the effectiveness of Phylo-HMGP. Importantly, we applied Phylo-HMGP to analyze a new cross-species DNA replication timing (RT) dataset from the same cell type in five primate species (human, chimpanzee, orangutan, gibbon, and green monkey). We demonstrate that our Phylo-HMGP model enables discovery of genomic regions with distinct evolutionary patterns of RT. Our method provides a generic framework for comparative analysis of multi-species continuous functional genomic signals to help reveal regions with conserved or lineage-specific regulatory roles.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 16, 2018.
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Continuous-trait probabilistic model for comparing multi-species functional genomic data
Yang Yang, Quanquan Gu, Yang Zhang, Takayo Sasaki, Julianna Crivello, Rachel J. O’Neill, David M. Gilbert, Jian Ma
bioRxiv 283093; doi: https://doi.org/10.1101/283093
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Continuous-trait probabilistic model for comparing multi-species functional genomic data
Yang Yang, Quanquan Gu, Yang Zhang, Takayo Sasaki, Julianna Crivello, Rachel J. O’Neill, David M. Gilbert, Jian Ma
bioRxiv 283093; doi: https://doi.org/10.1101/283093

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