Medical implications of technical accuracy in genome sequencing

open access (Genome Medicine)

Methods

We examine the relationship between human genome complexity and genes/variants reported to be associated with human disease. Specifically, we map regions of medical relevance to benchmark regions of high or low confidence. We use benchmark data to assess the sensitivity and positive predictive value of two representative sequencing pipelines for specific classes of variation.

 In one example of a false positive from our systematic error call set, one sequencing chemistry and one pipeline called a recognized, pathogenic frameshift deletion in BRCA2. Pathogenic variants in the BRCA genes are implicated in hereditary breast and ovarian cancer syndrome (http://www.ncbi.nlm.nih.gov/books/NBK1247/). The variant, rs80359760, is currently categorized in ClinVar as pathogenic/likely pathogenic based on several entries from the Breast Cancer Information Core, the Sharing Clinical Reports Project, and the literature (http://www.ncbi.nlm.nih.gov/clinvar/variation/52831/). Based on GIAB’s consensus sequence, this variant is known to be a false positive call for this patient. However, it might be reported to another patient as an incidental finding, and one with evidence for pathogenicity that might even lead to medical action. Examples like this highlight the importance of confirmatory testing by an orthogonal method. Additionally, we hope that our analyses and the reference materials can provide helpful meta-data for bioinformatics analysis of loci such as these, since this dataset allows positions with systematic biases and medically relevant annotations in public databases to be identified [44, 45].