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Ancestral Population Genomics with Jocx, a Coalescent Hidden Markov Model
Jade Yu Cheng1, Thomas Mailund2
1Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
Methods in Molecular Biology (Clifton, N.J.)
|January 25, 2020
Summary
Coalescence theory helps understand past population demographics. Recombination allows deeper insights into ancient speciation events by revealing historical coalescence patterns.
Area of Science:
- Population Genetics
- Evolutionary Biology
- Genomics
Background:
- Coalescence theory analyzes past population demographics from genetic samples.
- Tracing genetic lineages back in time reveals demographic history through coalescence rates.
- Limitations exist in exploring deep past demographics due to decreasing lineages.
Purpose of the Study:
- To investigate ancient speciation events using genetic data.
- To overcome limitations in deep coalescence analysis.
- To present a novel tool for inferring demographic parameters in ancient speciation.
Main Methods:
- Utilizing recombination to access deeper historical genetic data.
- Scanning genomic alignments to observe sequential coalescence processes at speciation.
- Employing coalescence hidden Markov models (HMMs).
Main Results:
- Recombination provides a window into ancient speciation events.
- Coalescence time patterns at speciation are preserved and do not erode.
- The tool Jocx, based on HMMs, can infer demographic parameters from these patterns.
Conclusions:
- Recombination is crucial for studying ancient speciation events.
- Coalescence hidden Markov models offer a framework for deep historical demographic inference.
- The Jocx tool facilitates the analysis of ancient speciation dynamics.
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