Genomics AI
Whole genomes from a day to under an hour with Parabricks-backed secondary analysis. Turn raw sequencing data into clinical-grade variant calls same-shift.
Product capabilities
Helix runs NVIDIA Parabricks pipelines to compress days of CPU-based analysis into minutes, with validated concordance and seamless integration into clinical labs.
Run alignment, variant calling, and annotation in under 60 minutes with Parabricks — replacing overnight CPU workflows with same-shift results. Validated for clinical use with 99.9% concordance to GATK best practices.
Pre-configured workflows for rare disease, oncology, and pharmacogenomics with validated quality metrics.
Link variant calls to imaging phenotypes, pathology, and clinical timelines for richer interpretation.
ClinVar, gnomAD, COSMIC, dbSNP, and custom knowledge bases with pathogenicity scoring.
VPC or on-prem with audit trails, model versioning, and PHI boundaries for clinical-grade compliance.
Variant review feedback flows back into Atlas for model retraining and knowledge base expansion.
NVIDIA healthcare stack
GPU-accelerated genomic analysis toolkit — alignment, variant calling, annotation, and quality control.
Drop-in replacement for CPU-based GATK workflows with validated concordance and clinical-grade outputs.
Performance metrics
Whole genome secondary analysis (30x WGS) from FASTQ to annotated VCF
Faster than CPU-based GATK pipelines — same-shift results instead of overnight runs
Concordance with GATK best practices on validated benchmark datasets
Lab throughput increase without new sequencers or staff — bottleneck shifts from compute to interpretation
Audit trail coverage for pipeline versions, reference genomes, and variant calls
Use cases
Turn around WGS results same-shift instead of days. Helix runs Parabricks pipelines to compress alignment, variant calling, and annotation from 18+ hours on CPUs to under 60 minutes on GPUs — with validated concordance and clinical-grade outputs.
Prioritize candidate variants for undiagnosed patients with phenotype-matched filtering and knowledge base lookup.
Extract PGx variants for CYP enzymes, drug transporters, and HLA alleles with automated reporting.
Detect somatic mutations, copy number alterations, and structural variants for precision oncology. Link genomic findings to imaging and pathology via Atlas for integrated molecular tumor boards.
Process thousands of genomes for GWAS, polygenic risk scores, and ancestry inference with scalable GPU infrastructure.
How it works
Helix connects to your sequencing infrastructure and applies GPU-accelerated Parabricks pipelines to every stage of secondary analysis.
Pull FASTQ from sequencer, LIMS, or object store via API or S3 sync
GPU-accelerated BWA-MEM alignment to GRCh38 reference genome
HaplotypeCaller for germline, Mutect2 for somatic, with GPU acceleration
Annotate with ClinVar, gnomAD, COSMIC, dbSNP, and pathogenicity scores
Link to Atlas for imaging, pathology, and clinical timeline context
Geneticist confirms, re-classifies, or escalates via workbench or LIMS push
Integration
Pull sample metadata, push results, and update case status via API
Ingest FASTQ from S3, GCS, Azure Blob, or on-prem NAS
Push structured genomic reports to Epic, Cerner, or FHIR endpoints
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FAQ
Answers for genomics lab directors, bioinformaticians, and compliance teams evaluating Helix.
Helix uses NVIDIA Parabricks, which has been validated for clinical genomics with 99.9% concordance to GATK best practices on benchmark datasets. Final validation for clinical reporting depends on your lab's CAP/CLIA requirements and workflow configuration.
Illumina, PacBio, and Oxford Nanopore. We support FASTQ and unaligned BAM ingest with configurable quality filtering and adapter trimming.
Yes. Helix runs in VPC, on-prem DGX, or hybrid configurations with full audit trails and PHI boundaries via Mergic Citadel.
Bi-directional API integration for sample metadata, pipeline status, and results delivery. We support all major LIMS vendors and can build custom connectors.
Get started
Bring a clinical, research, or population genomics use case. We'll map the GPU architecture, LIMS integration, and first measurable outcome.