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GADMA2: more efficient and flexible demographic inference from genetic data.

Ekaterina NoskovaNikita AbramovStanislav IliutkinAnton SidorinPavel DobryninVladimir I Ulyantsev
Published in: GigaScience (2023)
We demonstrate the better performance of a genetic algorithm in GADMA2 by comparing it to the initial version and other existing optimization approaches. Our experiments on simulated data indicate that GADMA2's likelihood engines are able to provide accurate estimations of demographic parameters even for misspecified models. We improve model parameters for 2 empirical datasets of inbred species.
Keyphrases
  • electronic health record
  • genome wide
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  • copy number
  • deep learning
  • high resolution
  • single cell
  • data analysis
  • artificial intelligence
  • neural network