Mathematics
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Department of Mathematics & Statistics
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Timothy Bilton

Studying for Doctor of Philosophy

Area of study:
Developing statistical methods for genetic analysis using genotyping-by-sequencing data

Supervisor: Matthew Schofield


Email: tbilton@maths.otago.ac.nz  


Thesis

Title: Developing statistical methods for genetic analysis using genotyping-by-sequencing data

Supervisors: Matthew Schofield, Ken Dodds (AgResearch) and Mik Black

Previous Degrees:

  • BSc in Mathematics & Statistics (Massey University),
  • BSc(Hons) in Statistics (Massey University).

Genotyping-by-sequencing (GBS) is a relatively new genotyping procedure that is generic, affordable and does not rely on the development of species-specific tools. However, for GBS data, each variant call has an associated error probability of a true heterozygous genotyping call being miscalled as homozygous, due to only one allele being read. At low depth, when a base has been sequenced in relatively few reads, a miscalled heterozygote is particularly problematic. Typically, this genotyping error is minimized by sequencing to high depths and filtering out genotype calls for variants with low read depth, although this results in fewer genotyped individuals or SNP’s being available for analysis. My PhD research consists of developing statistical methods to perform genetic analysis using the full GBS data, including genotype calls based on low read depth, by modelling the called genotypes as a function of the true genotypes and read depths. Areas of genetic analysis considered in my research are linkage mapping, relatedness matrix estimation and polyploidy species.