PT  - JOURNAL ARTICLE
AU  - Andrew Whalen
AU  - Gregor Gorjanc
AU  - John M Hickey
TI  - Parentage assignment with genotyping-by-sequencing data
AID  - 10.1101/270561
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 270561
4099  - http://biorxiv.org/content/early/2018/09/25/270561.short
4100  - http://biorxiv.org/content/early/2018/09/25/270561.full
AB  - In this paper we evaluate using genotype-by-sequencing (GBS) data to perform parentage assignment in lieu of traditional array data. The use of GBS data raises two issues: First, for low-coverage GBS data, it may not be possible to call the genotype at many loci, a critical first step for detecting opposing homozygous markers. Second, the amount of sequencing coverage may vary across individuals, making it challenging to directly compare the likelihood scores between putative parents. To address these issues we extend the probabilistic framework of Huisman (2017) and evaluate putative parents by comparing their (potentially noisy) genotypes to a series of proposal distributions. These distributions describe the expected genotype probabilities for the relatives of an individual. We assign putative parents as a parent if they are classified as a parent (as opposed to e.g., an unrelated individual), and if the assignment score passes a threshold. We evaluated this method on simulated data and found that (1) high-coverage GBS data performs similarly to array data and requires only a small number of markers to correctly assign parents and (2) low-coverage GBS data (as low as 0.1x) can also be used, provided that it is obtained across a large number of markers. When analysing the low-coverage GBS data, we also found a high number of false positives if the true parent is not contained within the list of candidate parents, but that this false positive rate can be greatly reduced by hand tuning the assignment threshold. We provide this parentage assignment method as a standalone program called AlphaAssign.