From raw sequencing reads to signed clinical reports. Golden Helix provides the complete NGS analysis software stack for diagnostic laboratories running panels, exomes, and whole genomes at clinical scale.
NGS analysis moves through three computational stages. Each requires purpose-built software, and in a clinical laboratory, each stage has requirements that research-grade tools were not designed to meet.
Secondary analysis transforms raw FASTQ files into a variant call file. Read alignment, duplicate marking, base quality recalibration, and variant calling across SNVs, indels, CNVs, and structural variants.
Golden Helix partners with Sentieon for a deterministic, fully validated reimplementation of the GATK best-practices pipeline. Sentieon delivers 10x to 50x faster processing than standard GATK while producing mathematically identical results.
Explore SentieonTertiary analysis is where the diagnostic work happens. A whole exome run produces 25,000 to 40,000 variant calls. A whole genome produces millions. The software reduces that list to clinically actionable findings through annotation, filtering, phenotype-driven prioritization, ACMG/AMP classification, and clinical report generation.
VarSeq handles the complete tertiary analysis workflow for germline, somatic, pharmacogenomic, and copy number variant analysis in one validated environment.
Explore VarSeqWithout a data warehouse, every case starts from scratch. With one, a laboratory builds an internal allele frequency database, a shared variant assessment catalog, and automated reclassification monitoring that alerts clinicians when external databases change classifications of variants previously seen in their patients.
VSWarehouse integrates directly with VarSeq to provide centralized assessment catalogs, reclassification monitoring, LIMS/EHR integration, and cohort analytics.
Explore VSWarehouseNot all NGS analysis software is built for clinical use. Research-grade tools, including many widely used open-source pipelines, were designed for exploratory analysis in academic settings. Deploying them in a CAP/CLIA-accredited clinical laboratory without substantial additional infrastructure and validation creates analytical, regulatory, and patient safety risks. The seven criteria below should form the basis of any laboratory's software evaluation.
Clinical laboratories must reproduce any result on demand. A pipeline that produces different outputs on different runs, due to random sampling, stochastic algorithms, or non-deterministic sorting, is not compliant with CAP/CLIA requirements. Every component must be version-locked, containerized, and validated for reproducibility.
Variant interpretation is only as good as the databases it draws on. ClinVar, gnomAD, OMIM, and ClinGen update continuously. Monthly-curated annotation updates ensure clinical decisions draw on current evidence. Golden Helix maintains monthly curated updates across all primary annotation sources, with versioned snapshots so every result is traceable to the exact database state used at analysis time.
Every variant assessment, every filter chain applied, every classification decision must be logged and permanently retrievable. CAP inspectors require labs to reproduce and justify any historical result. Audit logging is not optional, it is a structural requirement of the platform.
Manually applying the 28 ACMG/AMP classification criteria introduces inconsistency across reviewers, extends turnaround time, and creates documentation gaps. Automated criteria scoring calibrated to current ClinGen specifications, applied consistently across every case, cuts per-case interpretation time substantially while improving classification consistency.
A clinical NGS platform must handle every clinically relevant variant type in one environment: SNVs, indels, CNVs, structural variants, pharmacogenomic star alleles, and repeat expansions. Platforms that handle SNVs and indels but need separate tools for CNVs or PGx create analytical gaps, audit trail fragmentation, and validation overhead.
Genomic data is protected health information. A clinical NGS platform must support on-premises deployment for institutions with strict data sovereignty requirements, BYOC for institutions wanting cloud scalability without shared infrastructure, and air-gapped deployment for highly regulated environments. A single deployment model does not fit the diversity of clinical contexts.
Software deployed in a clinical laboratory should be developed and maintained under a certified QMS. An ISO 13485-certified QMS provides controlled release processes, change management documentation, post-market surveillance, and audit-ready records, the same standards clinical device manufacturers are held to. Golden Helix operates under an ISO 13485-certified QMS. All VarSeq releases are validated, version-controlled, and supported with change documentation appropriate for laboratory QMS integration. VarSeq Dx is CE marked under IVDR 2017/746.
Most laboratories assemble their NGS analysis infrastructure from disconnected tools: a secondary pipeline from one vendor, a tertiary platform from another, a separate data warehouse, and spreadsheet-based classification in between. Every interface between tools is a potential audit gap, a validation burden, and a source of error.
Golden Helix provides an integrated alternative: Sentieon for secondary analysis, VarSeq for tertiary analysis and clinical reporting, and VSWarehouse for enterprise data management. All designed to work together, all developed under the same ISO 13485-certified QMS, all supporting the same deployment models.
| Component | Function | Output |
|---|---|---|
| Sentieon | Secondary analysis: alignment, variant calling | BAM, VCF |
| VarSeq | Tertiary analysis: annotation, filtering, ACMG/AMP classification, reporting | Annotated VCF, clinical report |
| VSWarehouse | Data management: assessment catalogs, reclassification monitoring, LIMS/EHR integration | Institutional variant knowledgebase |
VarSeq accepts VCF input from any secondary analysis pipeline: DRAGEN, GATK, DeepVariant, Sentieon, or laboratory-developed pipelines. Labs already running a validated secondary workflow can adopt VarSeq for tertiary analysis without replacing existing infrastructure. VarSeq is also sequencer-agnostic, processing data from Illumina, PacBio, Oxford Nanopore, and other platforms, so labs can evaluate long-read NGS without rebuilding interpretation and reporting workflows.
VarSeq's workflows cover the major clinical NGS indications. Each application has dedicated filter chains, classification frameworks, and report templates.
Germline workflows for panels, WES, and WGS in rare disease diagnosis. Native trio analysis with automated de novo detection and compound heterozygosity confirmation. HPO-driven phenotype prioritization reduces interpretive burden for complex cases.
Rare Disease Analysis SoftwareSomatic variant analysis supports tumor-normal paired and tumor-only workflows with AMP/ASCO/CAP-guided classification, OncoKB and CIViC integration, TMB and MSI calculation, and therapeutic matching. Germline secondary findings during tumor profiling are flagged for counseling referral.
Precision Oncology SoftwareCarrier and prenatal panels require high-throughput processing, accurate CNV detection, and automated reporting at scale. VarSeq supports population-scale carrier screening programs with templated workflows, batch processing, and automated report generation for common recessive condition panels.
Prenatal & Carrier ScreeningThe PGx module performs star allele calling for CYP2D6, CYP2C19, DPYD, TPMT, NUDT15, and other pharmacogenomically relevant genes, using CPIC and FDA evidence-based recommendations to generate patient-specific drug-gene interaction reports.
Pharmacogenomics SoftwareNGS analysis software for clinical labs: stages, validation, deployment, and integration.
NGS analysis software refers to the computational tools used to process, analyze, and interpret next generation sequencing data. The term covers three distinct stages: secondary analysis software that transforms raw sequencing reads into variant calls (FASTQ to VCF), tertiary analysis software that annotates, filters, classifies, and reports those variants in a clinical context, and data management software that stores variant assessments and supports institutional knowledge building over time.
In a clinical laboratory, NGS analysis software must meet specific requirements for determinism, annotation currency, audit traceability, and regulatory compliance that research-grade tools are not designed for.
Secondary analysis software handles the computational pipeline from raw sequencing reads to variant calls: aligning reads to the reference genome, calling variants, and producing a VCF file. It answers the question: what variants are present?
Tertiary analysis software handles everything after the VCF: annotating variants with clinical database information, filtering candidates, applying ACMG or AMP classification criteria, and generating a signed clinical report. It answers the question: which variants are clinically significant? Both stages require dedicated, validated software in a clinical setting, and the quality of the tertiary analysis platform has a larger impact on diagnostic yield than the choice of secondary pipeline.
Yes. Before any NGS analysis software is used to generate clinical results, it must be analytically validated under CAP/CLIA requirements. Validation demonstrates that the pipeline performs as expected for the variant types and genomic regions it is intended to cover, establishing sensitivity, specificity, precision, and reproducibility on characterized reference materials.
The software must also be deterministic: the same input files must produce the same output on every run. CAP/CLIA accreditation requires that the laboratory can reproduce any historical result on demand, which requires version-locked, validated pipeline components with full audit trail documentation.
Clinical-grade NGS analysis software should detect all major variant types relevant to the clinical indication: single nucleotide variants (SNVs), small insertions and deletions (indels), copy number variants (CNVs), structural variants, pharmacogenomic star alleles, and for whole genome applications, repeat expansions.
Not all platforms handle all variant types. Some are optimized for SNV and indel calling but require separate tools for CNV detection or PGx analysis. Laboratories should evaluate whether a platform handles every relevant variant type in one validated environment, since multi-tool workflows create audit trail fragmentation and increase validation burden.
Clinical NGS software should support on-premises deployment for laboratories with strict data sovereignty requirements or institutional policies against cloud-based PHI storage, private cloud deployment (bring-your-own-cloud / BYOC) for laboratories that want cloud scalability with full administrative control, and air-gapped deployment for highly regulated or classified environments.
Most laboratories today require on-premises or BYOC deployment to meet HIPAA requirements and institutional data governance policies. Platforms that offer only shared multi-tenant cloud deployment may not be appropriate for clinical PHI without a signed Business Associate Agreement and careful review of the vendor's security controls.
Clinical NGS analysis software typically integrates with laboratory information management systems (LIMS) and electronic health records (EHR) through standardized APIs, HL7 FHIR messaging, or direct database connectors. Integration enables automated sample tracking, result delivery, and billing workflows without manual data re-entry.
When evaluating NGS software, labs should assess whether the vendor provides documented integration specifications, supports the LIMS and EHR systems already in use at the institution, and offers professional services support for integration implementation. Labs should also consider whether the software supports role-based access control integration with institutional identity management systems (SAML, LDAP, Active Directory) for automated user provisioning and deprovisioning.
Clinical NGS software is designed and validated for use in producing clinical results that directly affect patient care. It must meet specific regulatory requirements: determinism, audit traceability, version-locked pipeline components, and analytical validation documentation, that research-grade tools are not designed to provide.
Research NGS software is optimized for flexibility, exploratory analysis, and publication reproducibility, not for the regulatory compliance and operational reliability that clinical use requires. Many excellent research tools, including widely used open-source pipelines, can be used as components in a clinical pipeline with substantial additional validation and infrastructure, but deploying them without that validation in a CAP/CLIA-accredited laboratory creates significant regulatory risk.
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Diagnostic laboratories worldwide use Golden Helix to automate NGS workflows, improve diagnostic yield, and deliver signed clinical reports faster.