bioRxivBioinformaticsPreprint
Population networks from DNA sequences: methodological developments
Brigitte Schaeffer, Violaine NicolasiD, Frédéric AusterlitziD, Catherine Larédo
Abstract
Several classes of methods have been proposed for inferring the history of populations from genetic polymorphism data. As connectivity is a key factor to explain the structure of populations, several graph-based methods have been developed to this aim, using population genetics data. Here we propose an original method based on graphical models that uses DNA sequences to provide relationships between populations. We tested our method on various simulated data sets, describing typical demographic scenarios, for different parameters values. We found that our method behaved noticeably well for realistic demographic evolutionary processes and recovered suitably the migration processes. Our method provides thus a complementary tool for investigating population history based on genetic material.
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Inferring Migration Networks with Time-Lagged F2 Statistics
Giulio Isacchini, Takashi Okada, … Oskar Hallatschek·bioRxiv·Mar 12, 2026
- Inference and analysis of population structure using genetic data and network theory
Gili Greenbaum, Alan R. Templeton, Shirli Bar-David·bioRxiv·Feb 3, 2016
- Demographic inference using genetic data from a single individual: separating population size variation from population structure
Olivier Mazet, Willy Rodríguez, Lounès Chikhi·bioRxiv·Nov 27, 2014
- On the limits of fitting complex models of population history to genetic data
R. Maier, P. Flegontov, … D. Reich·bioRxiv·May 8, 2022
- GADMA: Genetic algorithm for inferring demographic history of multiple populations from allele frequency spectrum data
E. Noskova, V. Ulyantsev, … P. Dobrynin·bioRxiv·Jan 11, 2019
- Inference of complex population histories using whole-genome sequences from multiple populations
M. Steinrücken, J. Kamm, … Y. S. Song·bioRxiv·Sep 16, 2015