Blindspot Genetics — Evidence Base

The scale of the problem

Independent clinical studies establish that a meaningful share of pathogenic variants and Mendelian diagnoses are missed for technical, not biological, reasons.

Clinical scale & diagnostic impact

1 in 7

In clinical testing of 450,000+ patients, 13.8% of P/LP variants were technically challenging to detect by standard NGS — across segmental duplications, low-complexity regions, large indels, and CNVs (Lincoln et al. 2021, Genet Med).

PMID 34007000

1 in 3

In 4,577 molecularly characterized families, 34.3% encountered at least one diagnostic challenge — and applying a systematic framework to negative clinical sequencing reports resolved a substantial share of cases (AlAbdi et al. 2023, Nat Commun).

PMID 37644014

UDN

In an NIH Undiagnosed Diseases Network study, most participants could have been diagnosed with available clinical methods — the bottleneck was knowledge about test selection and gene-specific technical limitations (Cope et al. 2020, Mol Genet Genomic Med).

PMID 32730690

Caveats

Ten years of clinical whole-exome sequencing surfaced systematic mistakes and caveats — including alternate-contig multi-mapping artifacts and annotation drift as new transcripts are added (Corominas et al. 2022, Hum Mutat).

PMID 35191116

Sequencing methods & dead zones

HiFi

PacBio HiFi/CCS long reads resolve 152 of 193 medically-relevant NGS-problematic genes to 100% mappability — including GBA, PKD1, STRC, PMS2, and MYH7 — and achieve >99.9% SNV precision and recall vs GIAB benchmark (Wenger et al. 2019, Nat Biotechnol).

PMID 31406327

487

An exome-wide NGS dead-zone catalog defines genes impossible to analyze by standard NGS; 487 of them fall within the 4,964-gene medically-relevant panel. Four homology types are defined: same gene, different functional gene, pseudogene, non-CDS (Mandelker et al. 2016, Genet Med).

doi:10.1038/gim.2016.58

Dead zones

The same catalog identifies genes where even Sanger sequencing fails to provide orthogonal confirmation — a reminder that a "confirmatory" method can share the blind spot of the primary assay.

Mandelker et al. 2016

Reference assemblies & liftover

T2T

The first complete, gapless human genome sequence (T2T-CHM13) — the reference against which Blindspot computes assembly comparison and liftover analysis (Nurk et al. 2022, Science).

PMID 35357919

46.9%

A complete reference genome improves analysis of human genetic variation — the source for GRCh38-vs-CHM13 discordance, false-duplication gene pairs, and the medically-relevant gene impact table (Table S13) that Blindspot draws on (Aganezov et al. 2022, Science).

PMID 35357935

239

ClinVar liftover failures tracked in Blindspot's own Picard LiftoverVcf run — 239 P/LP variants cannot be located in T2T-CHM13, a reconstructed rate of ≈0.07% of GRCh38 P/LP variants.

NCBI ClinVar · internal pipeline

Reference datasets

GIAB

Genome in a Bottle difficult-region stratification (v3.6) — the segmental-duplication, GC-extreme, low-mappability, and tandem-repeat categories that drive Blindspot's exon-level overlays.

NIST Benchmark

MANE

MANE Select and RefSeq Select transcripts provide the exon / CDS / UTR structure overlaid on difficult regions — so a blind spot can be located to the exon, not just the gene.

NCBI / EMBL-EBI MANE

ClinGen

Gene–disease validity classifications and dosage-sensitivity curation — including refuted associations that flag genes that shouldn't be reported on a given panel.

clinicalgenome.org

ClinVar

The ClinVar 2026-05-30 release underpins Blindspot's pathogenic/likely-pathogenic variant set and the liftover-failure analysis across assemblies.

NCBI ClinVar

Built on peer-reviewed science, not vendor claims.

The scale of the problem

Trace any flag to its source.