  Motivation: Whole-genome high-coverage sequencing has been widely used for
personal and cancer genomics as well as in various research areas. However, in
the lack of an unbiased whole-genome truth set, the global error rate of
variant calls and the leading causal artifacts still remain unclear even given
the great efforts in the evaluation of variant calling methods.
  Results: We made ten SNP and INDEL call sets with two read mappers and five
variant callers, both on a haploid human genome and a diploid genome at a
similar coverage. By investigating false heterozygous calls in the haploid
genome, we identified the erroneous realignment in low-complexity regions and
the incomplete reference genome with respect to the sample as the two major
sources of errors, which press for continued improvements in these two areas.
We estimated that the error rate of raw genotype calls is as high as 1 in
10-15kb, but the error rate of post-filtered calls is reduced to 1 in 100-200kb
without significant compromise on the sensitivity.
  Availability: BWA-MEM alignment: http://bit.ly/1g8XqRt; Scripts:
https://github.com/lh3/varcmp; Additional data:
https://figshare.com/articles/Towards_better_understanding_of_artifacts_in_variating_calling_from_high_coverage_samples/981073
