Related Experiment Video
Updated: Jul 9, 2025
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
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link-ancestors: fast simulation of local ancestry with tree sequence software
Georgia Tsambos1,2,3, Jerome Kelleher4, Peter Ralph5
1School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, 3052, Australia.
Bioinformatics Advances
|November 30, 2023
Summary
Simulating realistic genetic ancestry tracts for inference is difficult. This study introduces an efficient algorithm to extract this data from tree sequences generated by msprime and SLiM simulations.
Area of Science:
- Population genetics
- Computational biology
- Bioinformatics
Background:
- Simulating large-scale genetic ancestry tracts is computationally intensive.
- Accurate simulation is crucial for simulation-based inference in population genetics.
Purpose of the Study:
- To present an efficient algorithm for extracting genetic ancestry information from tree sequences.
- To enable scalable simulation-based inference of population genetic models.
Main Methods:
- Developed a novel algorithm for extracting genetic ancestry tracts.
- Utilized tree sequences generated by msprime and SLiM simulations.
- Implemented the algorithm in C and provided a Python wrapper (link-ancestors in tskit and tspop).
Main Results:
- The algorithm efficiently extracts genetic ancestry information from large tree sequences.
- Enables the simulation of realistic genetic ancestry tracts at scale.
- The implementation is publicly available in tskit and tspop.
Conclusions:
- The presented algorithm significantly improves the efficiency of simulating genetic ancestry for inference.
- Facilitates more complex and scalable population genetic studies.
- Provides accessible tools for researchers in computational biology and bioinformatics.
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