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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Sampletrees and Rsampletrees: sampling gene genealogies conditional on SNP genotype data.

Kelly M Burkett¹, Brad McNeney², Jinko Graham²

¹Department of Statistics, Simon Fraser University, Burnaby V5A 1S6, Canada and Department of Mathematics and Statistics, University of Ottawa, Ottawa K1N 6N5, Canada.

Bioinformatics (Oxford, England)

|January 21, 2016

Summary

This summary is machine-generated.

The sampletrees program uses Markov chain Monte Carlo to sample gene genealogies from SNP genotype data. Its companion R package, Rsampletrees, aids in file processing and output visualization.

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Area of Science:

Population genetics
Computational biology

Background:

Gene genealogies are crucial for understanding evolutionary history.
Analyzing genetic data requires efficient computational tools.

Purpose of the Study:

To introduce sampletrees, a novel Markov chain Monte Carlo sampler for gene genealogies.
To present Rsampletrees, a companion R package for data management and visualization.

Main Methods:

sampletrees employs Markov chain Monte Carlo methods.
It handles both phased and unphased SNP genotype data.
Rsampletrees facilitates pre- and post-processing of sampletrees output.

Main Results:

sampletrees enables the sampling of gene genealogies.
Rsampletrees provides tools for file setup, storage, and plotting.
The software is implemented in C++ and available with documentation.

Conclusions:

sampletrees and Rsampletrees offer a comprehensive solution for gene genealogy analysis.
These tools enhance the study of population genetics and evolutionary processes.