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• W2789324785 abstract "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." @default.
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• W2789324785 date "2018-03-16" @default.
• W2789324785 modified "2023-09-26" @default.
• W2789324785 title "Continuous-trait probabilistic model for comparing multi-species functional genomic data" @default.
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• W2789324785 doi "https://doi.org/10.1101/283093" @default.
• W2789324785 hasPublicationYear "2018" @default.
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