ARGON: fast, whole-genome simulation of the discrete time Wright-fisher process.

Bioinformatics

Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.

Published: October 2016

Motivation: Simulation under the coalescent model is ubiquitous in the analysis of genetic data. The rapid growth of real data sets from multiple human populations led to increasing interest in simulating very large sample sizes at whole-chromosome scales. When the sample size is large, the coalescent model becomes an increasingly inaccurate approximation of the discrete time Wright-Fisher model (DTWF). Analytical and computational treatment of the DTWF, however, is generally harder.

Results: We present a simulator (ARGON) for the DTWF process that scales up to hundreds of thousands of samples and whole-chromosome lengths, with a time/memory performance comparable or superior to currently available methods for coalescent simulation. The simulator supports arbitrary demographic history, migration, Newick tree output, variable mutation/recombination rates and gene conversion, and efficiently outputs pairwise identical-by-descent sharing data.

Availability: ARGON (version 0.1) is written in Java, open source, and freely available at https://github.com/pierpal/ARGON CONTACT: ppalama@hsph.harvard.edu

Supplementary Information: Supplementary data are available at Bioinformatics online.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191159PMC
http://dx.doi.org/10.1093/bioinformatics/btw355DOI Listing

Publication Analysis

Top Keywords

discrete time
8
time wright-fisher
8
coalescent model
8
argon fast
4
fast whole-genome
4
whole-genome simulation
4
simulation discrete
4
wright-fisher process
4
process motivation
4
motivation simulation
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!