Janine Wright
University of Otago
The use of genetic tags (from non-invasive samples such as hair and faeces) to identify individual animals is increasingly common in wildlife studies. Non-invasive genetic sampling has many advantages and huge potential, but while it is possible to generate significant amounts of data from these samples, the biggest challenge in the application of the approach is overcoming inherent errors. Genotyping errors arise when the poor sample quality due to an insufficient quantity of DNA leads to failure of DNA amplification at one or more loci. This has the effect of heterozygous individuals being scored as homozygotes at those loci as only one allele is detected (termed 'allelic drop-out'). False alleles are also possible. Error rates will be species-specific, and will depend on the source of samples and the way the samples have been handled. If errors go undetected and the genotypes are naively used in mark-recapture models, significant overestimates of population size can occur. Using data from the brush-tailed possum (Trichosurus vulpecula) in New Zealand and the European badger (Meles meles) we describe a method based on Bayesian imputation that allows us to model data from samples that include uncertain genotypes.
Session 3a, Statistical Genomics: 11:30 — 11:50, Room 445