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SIA: Selection Inference Using the Ancestral Recombination Graph
[article]
2021
bioRxiv
pre-print
Detecting signals of selection from genomic data is a central problem in population genetics. Coupling the rich information in the ancestral recombination graph (ARG) with a powerful and scalable deep learning framework, we developed a novel method to detect and quantify positive selection: Selection Inference using the Ancestral recombination graph (SIA). Built on a Long Short-Term Memory (LSTM) architecture, a particular type of a Recurrent Neural Network (RNN), SIA can be trained to
doi:10.1101/2021.06.22.449427
fatcat:2c7g4hkkjnas5ae4yjrs76nzzy