Assay
Variant Calling: sanity checks and pitfalls
Reads are aligned to a reference build, duplicates are marked, base quality scores may be recalibrated, and variants are called per sample or jointly across a cohort (GATK HaplotypeCaller, DeepVariant, bcftools). Then filtering, annotation and interpretation, where most of the judgment lives. The classic mistakes are mixing hg19 and hg38 coordinates, using a reference whose contig names do not match the annotation, trusting variants in low-mappability regions, and never running a sex or relatedness check that would have caught a sample swap.
Who this is for: Clinical and translational genomics analysts producing germline or somatic VCFs from exome or genome data, often under a pipeline they inherited. They need to know which variants are real, which are artifacts of alignment or mapping, and whether the sample they sequenced is the sample on the label.
- How to Detect Contamination in Variant Calling
A low mapping rate isn't "bad sequencing" until you've checked what the unmapped reads actually are.
- How to Catch a Genome Build Mismatch in Variant Calling
A BED file from the wrong build gives you confident, wrong overlaps, and the header check that catches it takes thirty seconds.
- How to Catch a Sample Swap in Variant Calling
X heterozygosity, chrY coverage and pairwise genotype concordance take minutes to compute and catch mislabels that no alignment or variant-quality QC report will ever flag.