Identify & Interpret Disease-Causing DNA Variants

Model non-coding regulatory disruptions, chromatin accessibility remodeling, and transcription factor binding loss with deep sequence delta predictions inspired by AlphaGenome.

Variant Locus

Benchmarked Clinical Presets

Target Gene / Locus

Reference Allele Alternative Allele

Consequence Category Upstream/Downstream Genomic Window (51 bp centered on variant) Click any nucleotide in the interactive rail to relocate the variant coordinate.

Variant Effect Assessment

chr5:1,295,228 C>T

● Pathogenic (Gain of ETS-binding)

5' ← Flanking Context → 3' (Variant highlighted in center) Offset: +0 bp

Model Log-Odds (ΔScore) +3.84 Significant de novo activation

Chromatin Openness +62% ATAC-seq signal surge

ACMG / AMP Category PS3 + PM2 Strong functional evidence

Predicted Epigenomic Profiles (Ref vs. Alt) DNAse-seq & Transcription Factor Occupancy

Transcription Factor Binding Motif Deltas

TF Motif	Position	Ref Affinity (PWM)	Alt Affinity (PWM)	Δ Binding	Mechanism Impact

Variant effect evaluated locally across 51 bp regulatory window.

Deep-Sequence Genomic Variant Prediction

Over 98% of the human genome consists of non-coding sequence. Conventional diagnostic pipelines often classify non-coding single-nucleotide variants (SNVs) as "Variants of Uncertain Significance" (VUS) due to the absence of direct amino acid coding changes. Deep sequence neural models (such as DeepMind's AlphaGenome) learn context-dependent regulatory syntax directly from hundreds of megabases of DNA.

Biological Mechanisms Modeled

De Novo Motif Creation: As seen in the TERT promoter mutation (C228T/C250T), a C>T substitution produces an 11-bp CCCGGAAGGGG consensus sequence, recruiting GABPα / ETS transcription factors that drive aberrant telomerase expression in glioblastoma and melanoma.

Chromatin Accessibility Remodeling: Nucleosome positioning, ATAC-seq hypersensitivity, and histone modifications (such as H3K27ac and H3K4me3) undergo measurable delta shifts when pioneer transcription factors are blocked or artificially created.

ACMG / AMP Diagnostic Interpretation

Clinical genomics guidelines demand functional validation (PS3) alongside computational evidence (PP3) and population frequency filtering (PM2). By pairing motif position weight matrices (PWMs) with multi-track deep accessibility scores, this workbench provides researchers and diagnostic geneticists with deterministic, reproducible variant interpretation dossiers.

How are Position Weight Matrices (PWMs) calculated in this workbench?

Each known transcription factor (ETS1, GABP, NF-kB, SP1, GATA1, TATA-box, FoxA1) is modeled via validated position frequency matrices derived from JASPAR and ENCODE. Log-odds affinity scores are evaluated continuously across both strands over the 51-bp window for both the reference and mutated allele.

Can I input custom FASTA sequences?

Yes. You can paste any DNA sequence into the flanking context textarea. The center base represents the variant position. Changing the sequence immediately recalculates motif alignments, chromatin accessibility tracks, and ACMG criteria.

Does this tool send patient or genetic data to an external server?

No. All calculations, motif alignments, and profile visualizations execute entirely client-side in your browser's local JavaScript environment, ensuring complete genomic data privacy.