Toward better understanding of artifacts in variant calling from high-coverage samples

By Heng Li. Bioinform., 2014

858 citations recorded by the source corpus.

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 10 single nucleotide polymorphism 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 10-15 kb, but the error rate of post-filtered calls is reduced to 1 in 100-200 kb without significant compromise on the sensitivity. AVAILABILITY AND IMPLEMENTATION BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp. CONTACT hengli@broadinstitute.org SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/02f77bb723cb84b95b39fa626962086bbccb32c4

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Citations in the corpus

Artificial intelligence in clinical and genomic diagnostics (2019, background): “Standard variant-calling tools are prone to systematic errors that are associated with the subtleties of sample preparation, sequencing technology, sequence context, and the sometimes unpredictable influence of biology such as somatic mosaicism [50].”
Mosdepth: quick coverage calculation for genomes and exomes (2017, background): “…of sequencing coverage is critical for genomic analyses such as calling copy-number variation (CNV), e.g. by cn.mops (Klambauer et al. , 2012), quality control (Pedersen et al. , 2017), and determining which genomic regions have too low, or too high (Li, 2014) coverage for reliable variant calling.”
The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes (2014, background): “The precision of the mapping approaches may be over-estimated for this dataset due to the absence of non-core sequence that is known to confound mapping [58].”
Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly (2016, neutral): “Comparison to GRCh37 and GRCh38 suggests that these new haploid assemblies may serve as more reliable substrates for variant calling than the reference assembly, although further analysis is needed to determinewhether improvements occur in genomic regions of interest.”