Structured Genomic Evidence Infrastructure
Structured aggregation of variant-level evidence for laboratory review and quality control.
Resonance Genomics develops structured genomic evidence systems for internal laboratory review and variant reanalysis workflows.
Available for research-use evaluation by qualified laboratories.
Designed for clinical genomics laboratories and research groups performing variant review, assay design, and reanalysis workflows.
Scientific Background
Workflows are developed and overseen by a clinical genomics scientist (MD, PhD) with over a decade of experience in diagnostic laboratory variant interpretation, assay design, and sequencing workflows.
All infrastructure is designed for research-use evaluation within established laboratory workflows.
WHAT WE BUILD
Modular genomic evidence infrastructure supporting assay design and variant review workflows.
Core infrastructure components include:
- Capture Design Review & Coverage Gap Assessment
- PCR Primer QC – gnomAD-aware pre-screening
- Intronic Variant Mapping for Panel Optimization
- Risk Allele Evidence Extraction
Capture Design Review & Coverage Gap Assessment
Resonance Genomics provides BED-based workflows to support evaluation of existing targeted panels and exome-slicing designs for coverage completeness and gap identification against standardized transcript frameworks (MANE Select and MANE Plus Clinical).
This includes assessment of:
- Pathogenic and likely pathogenic intronic loci curated from ClinVar, based on the current release
- Coding exons with incomplete or absent coverage
- Splice-adjacent regions using configurable padding (e.g., ±10–20 bp)
Outputs are delivered as standardized interval files suitable for comparison and integration into existing pipelines. Where needed, guidance or lightweight bioinformatic support can be provided to perform these assessments within a laboratory workflow.
PCR Primer QC Pre-screening
Independent quality control of PCR primers with emphasis on detecting common population variants within primer binding sites (gnomAD) — a known potential source of allele dropout or amplification bias in sequencing assays [1].
The analysis also evaluates primer locations relative to segmental duplication regions, where highly homologous genomic sequences may increase the risk of non-specific amplification [2]. In such regions, laboratories sometimes consider alternative strategies such as long-range PCR or locus-specific assay design.
Intronic Variant Mapping for Panel Optimization and Variant Discovery
Pathogenic variants located deep within introns can disrupt normal RNA splicing by activating cryptic splice sites or pseudo-exons, representing an increasingly recognized mechanism of genetic disease [3]. By systematically compiling intronic variants reported in ClinVar and mapping their genomic positions relative to MANE transcripts, this analysis highlights loci where noncoding variation has already been observed. These regions can be useful for evaluating capture designs, identifying potential gaps in sequencing panels, and prioritizing intronic loci for further investigation in both clinical and research studies.
Risk Allele Variant Extraction
Clinical laboratories are increasingly expected to consider variants associated with disease susceptibility in addition to traditional Mendelian pathogenic variants [5]. The ClinGen Low-Penetrance/Risk Allele Working Group has highlighted the need for dedicated approaches to capture and evaluate this class of variants. Resonance Genomics provides workflows that extract variants reported in resources such as the GWAS Catalog and ClinVar within genes of interest and compile structured tables linking genomic coordinates, database identifiers, and supporting publications, enabling laboratories to efficiently review and assess variants that may meet risk-allele criteria [4].
REFERENCES
- Blais J, et al. Risk of Misdiagnosis Due to Allele Dropout and False-Positive Genotyping Results. Journal of Molecular Diagnostics. 2015.
- Ghani M, Sato C, Rogaeva E. Segmental duplications in genome-wide significant loci and housekeeping genes; warning for GAPDH and ACTB. Neurobiology of Aging. 2013.
- Vaz-Drago R, Custódio N, Carmo-Fonseca M. Deep intronic mutations and human disease. Human Genetics. 2017.
- Schmidt RJ, et. Recommendations for Risk Allele Evidence Curation, Classification, and Reporting from the ClinGen Low Penetrance/Risk Allele Working Group. 2024
DATA SOURCES & ATTRIBUTION
Resonance Genomics infrastructure operates exclusively on publicly available and licensed data sources, including but not limited to:
- ClinVar public releases (NCBI)
- GWAS Catalog (European Bioinformatics Institute)
- gnomAD population frequency datasets
- PubMed-indexed literature
- Public computational annotation resources
All structured outputs maintain clear source attribution and release-version transparency.
GUIDELINE & THRESHOLD REFERENCE
Resonance Genomics does not apply guideline thresholds, assign evidence strengths, or perform interpretation. Laboratories should consult original guideline publications to determine relevant threshold values.
For reference:
https://cspec.genome.network/
SCOPE & OPERATIONAL BOUNDARIES
Resonance Genomics provides evidence aggregation and documentation support only.
- No clinical variant classification
- No diagnostic interpretation
- No assignment of pathogenicity
- No patient-identifiable data ingestion or storage
All services support internal laboratory research and review workflows.
PLATFORM PRINCIPLES
- Public-data-only processing and attribution
- Transcript-consistent evidence structuring
- Reproducibility and transparency in outputs
- No patient-identifiable data ingest or storage
- No clinical classification or interpretation provided
- Source-version documentation for updates
CONTROLLED INFRASTRUCTURE ACCESS
Services are available to research laboratories and clinical genomics groups upon request and institutional review.
Laboratory Evaluation
Resonance Genomics workflows are available for evaluation by research and clinical genomics laboratories interested in structured variant evidence aggregation and workflow optimization.
If your laboratory is interested in evaluating these tools or discussing potential collaboration, please contact us.