Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing

Inherent sources of error and bias that affect the quality of the sequence data include index hopping and bias towards the reference allele. The impact of these artefacts is likely greater for low-coverage data than for high-coverage data because low-coverage data has scant information and many standard tools for processing sequence data were designed for high-coverage data. With the proliferation of cost-effective low-coverage sequencing there is a need to understand the impact of these errors and bias on resulting genotype calls.
Results
We used a dataset of 26 pigs sequenced both at 2x with multiplexing and at 30x without multiplexing to show that index hopping and bias towards the reference allele due to alignment had little impact on genotype calls. However, pruning of alternative haplotypes supported by a number of reads below a predefined threshold, a default and desired step for removing potential sequencing errors in high-coverage data, introduced an unexpected bias towards the reference allele when applied to low-coverage data. This bias reduced best-guess genotype concordance of low-coverage sequence data by 19.0 absolute percentage points.
Conclusions
We propose a simple pipeline to correct this bias and we recommend that users of low-coverage sequencing be wary of unexpected biases produced by tools designed for high-coverage sequencing.