Table 1 Potential analytical sources of missed diagnoses and corresponding improvements made to the DDD workflow since 2014

Variant detection

Sequence data is mapped to the human genome reference, and variation called relative to that reference

Low-depth sequence dataIncorrect reference sequenceIncorrect mappingVariant detection/genotyping failedVariant class not considered (e.g., triplet repeats)

Updated versions of BWA, SAMtools, GATK, and DeNovoGearMultisample variant callingAdditional variant detection algorithms

Variant annotation and filtering

Stringent filters are applied to exclude low-quality, common, and noncoding variants that are unlikely to be clinically relevant

Low-quality variant discardedIncorrect annotation of allele frequencyIncorrect annotation of consequenceVariant filtering thresholds too stringent

Updated version of VEPUpdated MAF dataUpdated filtering thresholds (lower MAF, exclusion of benign inherited missense variants)

Gene prioritization

Evidence-based, disease-specific “virtual” gene panels are applied to limit variants to those with a relevant genotype (heterozygous/homozygous) and inheritance (dominant/recessive) in proven disease-causing genes

Incorrect disease mechanismIncorrect inheritance or family historyIncomplete penetrancePhenotype not recordedKnown gene missing from panelCausal gene not yet discovered

Updated DDG2P (November 2013 freeze used previously; June 2016 freeze used here, including 286 additional genes)Plausibly pathogenic variants shared via DECIPHER Research TrackReviewed parental phenotypes

Clinical assessment

Clinical assessment of the pathogenicity and contribution of specific variants to disease in a specific individual/family

Patient phenotype differs from previously published casesPhenotype not yet developedEvidence for pathogenicity is unclear

Candidate variants re-reviewed by core DDD clinical team and/or referring clinicianSome patients clinically assessed again