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Department of Mathematics & Statistics
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Josh Bromell

Studying for Master of Science

Area of study:
Methods for bias correction of SNP data generated using "genotyping by sequencing."

Supervisor: David Bryant



Title: Methods for bias correction of SNP data generated using "genotyping by sequencing."

Supervisors: David Bryant, Peter Dillingham

Previous Degrees:

  • Bachelor of Science in Mathematics and Genetics (Otago)
  • Bachelor of Science (Honours) in Mathematics (Otago)

Single Nucleotide Polymorphisms (SNPs) have become a standard source of genetic information about evolutionary relationships between species and ancestral demographics. A range of technological advances have made SNP data affordable and accessible for a wide range of species. For some applications, however, the fact that we are restricting attention to variable sites leads to a significant and potentially misleading source of bias when inferring population sizes or divergence times.

In this project we will explore a novel technique for correcting these biases when SNPs are generated through the widely used `genotyping by sequencing' method. The novelty stems from a strategy whereby different

likelihood functions are applied to different segments in the data, this being done in a way which maximizes power without distorting the inferred signal. Implementation of this approach will require the development of new mathematical and statistical theory. The new methods will be incorporated into the widely used BEAST2 package, and applied to a range of existing data sets.