PT  - JOURNAL ARTICLE
AU  - Miguel Navascués
AU  - Raphaël Leblois
AU  - Concetta Burgarella
TI  - Demographic inference through approximate-Bayesian-computation skyline plots
AID  - 10.1101/112060
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 112060
4099  - http://biorxiv.org/content/early/2017/03/02/112060.short
4100  - http://biorxiv.org/content/early/2017/03/02/112060.full
AB  - The skyline plot is a graphical representation of estimated past effective population size as a function of time. Its inference is based on models without an a priori assumption on a mathematical function determining the shape of the demographic change, typically a constant piecewise model. Because of this, it is considered to achieve a more realistic description of the complex demographies occurring in natural populations. Currently, there are implementations of the skyline plot based on coalescent samplers and a composite likelihood approach. In the present work we provide an equivalent implementation within the Approximate Bayesian Computation (ABC) framework and provide an assessment of its performance for microsatellite data. The method correctly retrieves the signal of contracting, constant and expanding populations, although the graphical shape of the plot is not always an accurate representation of true demographic trajectory. Because of the flexibility of ABC, similar approaches can be extended to other type of data, to models with multiple populations, or to other parameters that could change through time, such as the migration rate.