Bioinformatics Pipeline Engineering

NGS Pipeline Development Services for Clinical Labs & Life Science Organizations

Production-grade bioinformatics pipeline development - from raw sequencer output to clinically validated variant calls, engineered for reliability, scale, and long-term maintainability.

 
Talk to Our Bioinformatics Pipeline Engineering Experts →

Pipeline Run #NX-20240506-WGS-001

Status: Running · 42 samples · Started 09:12 UTC

FASTQ

Ingestion

→
Align

BWA-MEM2

→
Call

HaplotypeCaller

→
Annotate

VEP

Sample Progress

75%

32/42 samples complete · Est. completion 11:48 UTC

QC Dashboard

✓ Coverage: PASS

✓ Dup Rate: PASS

Cost Monitor

Cost/sample: $1.84

Total run: $77.28

Why Genomics Teams Come To Us

The problems we solve are not edge cases — they are the everyday reality of genomics teams trying to run research-grade pipelines in clinical-grade environments.

 

Pipelines Designed for Pilots, Not Production

Scripts that work at 10 samples break at 200. No retry logic. No observability. One failed sample stalls the entire run.

Version Drift and Reproducibility Failures

Tool versions shift, reference builds diverge, containers go undocumented. Results vary between runs without an audit trail.

No Visibility Into Cost-Per-Sample

Pipelines run as black boxes. Lab directors can’t answer: what does a WGS run cost? Where is the bottleneck? What’s the average TAT?

No Path from Pipeline to Clinic

Variant call files sit in object storage with no automated route to LIMS, reporting systems, or interpretation platforms.

Talk to Our Bioinformatics Pipeline Engineering Experts →
Our Approach

How We Engineer Bioinformatics Pipelines
That Hold Up in Production

We embed with your bioinformatics and platform teams to design, build, validate, and operate pipelines that meet the reliability and reproducibility standards of a clinical production environment. Four principles govern every engagement:

01.

Design-First Engineering

Architecture, framework selection (Nextflow, WDL, Snakemake), cloud vs HPC strategy, and reference data management — all decided and documented before a line of code is written.

02.

Production Engineering

Containerised environments, parameterised config, automated QC gates, failure detection with retry logic, and full audit logging per run. Built in as defaults — not bolted on later.

03.

Validation & Clinical Readiness

Benchmarked against NIST Genome in a Bottle and SEQC2 reference datasets. Analytical sensitivity, specificity, and concordance documented before production deployment.

04.

Long-Term Maintenance

Reference builds update. Tools release new versions. We maintain your pipelines, keeping them validated, up to date, and operationally sound so your team can focus on science, not infrastructure.

TECH STACK

Nextflow DSL2
WDL
Snakemake
Docker
Singularity
Kubernetes
AWS Batch
GCP Life Sciences
Azure Batch
Cromwell
GATK
BWA-MEM2
STAR
DeepVariant
Strelka2
Mutect2
VEP
ANNOVAR
SnpEff
Capabilities

What We Build: Full-Spectrum NGS Pipeline Development Services

Every engagement is different - assay type, scale, compute environment, downstream system. Here is the full range of what our bioinformatics pipeline development practice covers.

 
01 · WES & WGS

Whole Exome & Whole Genome Sequencing Pipeline Software

We build and maintain WES and WGS pipelines from FASTQ ingestion through alignment, germline and somatic variant calling, annotation, and QC reporting.

  • Primary analysis: adapter trimming (Fastp, Trimmomatic), alignment to GRCh37/GRCh38 (BWA-MEM2, Bowtie2), duplicate marking
  • Germline variant calling: GATK HaplotypeCaller, DeepVariant — single-sample and joint genotyping modes
  • Somatic variant calling: Mutect2, Strelka2, VarScan2 — ensemble approaches for clinical-grade sensitivity
  • Copy number analysis: GATK CNV, CNVKit, PURPLE for tumour purity and ploidy estimation
  • Structural variant detection: Manta, LUMPY, DELLY — tuned for clinical sensitivity thresholds
  • QC metrics: per-sample coverage, on-target rates, duplication rates — reported via MultiQC dashboards with automated pass/fail gates
Talk to a Pipeline Engineering Specialist →
02 · Somatic Calling

Somatic Variant Calling Pipeline Engineering

Somatic variant detection is technically demanding and clinically critical. We engineer somatic pipelines for comprehensive oncology and clinical coverage.

  • Tumour-normal paired and tumour-only workflows — with matched normal handling and Panel of Normals (PON) construction
  • Tumour purity and clonal evolution analysis for oncology applications
  • MSI and TMB calling, FFPE-aware variant filtering to reduce artefact rates in archival samples
  • SNV, indel, CNV, SV, and fusion event detection in a unified pipeline output
  • VCF annotation, tier classification, and formatting for downstream clinical interpretation tools
Talk to an Expert →
03 · RNA-Seq

RNA-Seq Analysis Pipeline Development

Transcriptomic workflows require a fundamentally different engineering approach from DNA-based pipelines. Our RNA-Seq development covers:

  • Splice-aware alignment (STAR, HISAT2) with reference annotation management (GENCODE, Ensembl, RefSeq)
  • Gene expression quantification (Salmon, featureCounts, RSEM) with batch effect awareness
  • Differential expression analysis pipelines (DESeq2, edgeR) integrated into the production workflow
  • Fusion gene detection (STAR-Fusion, Arriba) for oncology and rare disease applications
  • Single-sample and multi-cohort modes with appropriate normalisation strategies
Schedule a Call →
04 · Targeted Panel

Targeted Panel Pipeline Development

Clinical panel pipelines demand tighter requirements than research workflows — higher sensitivity thresholds, controlled QC, and regulatory traceability. We build for:

  • Amplicon-based and hybrid capture panel designs
  • Ultra-deep sequencing with allele-frequency sensitivity down to 0.5% VAF for liquid biopsy applications
  • Pharmacogenomics (PGx) panel pipelines with star allele calling — CPIC-compliant
  • Hereditary cancer, cardiology, and rare disease gene panels with ACMG-aligned variant output
  • Custom BED file management, panel versioning, and reference interval tracking
Let’s Talk →
05 · Annotation

Variant Annotation Pipeline Development

A variant call without annotation is a number without meaning. Our annotation stack covers:

  • Functional annotation: VEP, ANNOVAR, SnpEff — with configurable sources per assay type
  • Population frequency: gnomAD (v2/v3/v4), ClinVar, COSMIC, dbSNP, 1000 Genomes
  • In-silico pathogenicity: REVEL, CADD, SIFT, PolyPhen-2, AlphaMissense integration
  • Splice impact prediction: SpliceAI, MaxEntScan — critical for intronic and synonymous variant assessment
  • Oncology annotation: OncoKB, CGI, CIViC, COSMIC Tier 1 integration
  • Output formatting for downstream ACMG classification tools and structured ingestion by clinical reporting systems
Talk to an Expert →
06 · Workflow Frameworks

Nextflow, WDL & Snakemake Pipeline Development

We are fluent in all three major workflow languages — and we select the right one for your team, compute environment, and long-term maintenance reality.

ML-Assisted ACMG/AMP Classification

Evidence aggregation across ClinVar, gnomAD, in-silico tools, and internal lab history — surfaced at the variant level with confidence scores.

VUS Re-Analysis at Cohort Scale

Systematic re-evaluation of variants of uncertain significance as new evidence accumulates, with automated reclassification workflows and notification to ordering clinicians.

Phenotype-Driven Variant Prioritisation

HPO term integration to rank variants by clinical concordance before the interpreter opens the case.

Explainable AI Outputs

Every classification suggestion includes the evidence basis, the weight of each criterion, and a human-readable rationale — ensuring clinical teams can trust, verify, and sign off on AI-assisted interpretations.

Talk to a Pipeline Engineering Specialist →
07 · Operations

Pipeline Operations & Reliability Engineering

A pipeline that fails silently is worse than one that fails loudly. Operational reliability is built into every pipeline we deliver:

  • Kubernetes-native execution on EKS (AWS), GKE (GCP), or AKS (Azure) - auto-scaling node pools aligned to sample batch sizes
  • Automated failure detection with configurable retry logic - per-task retry counts, backoff strategies, and alerting on persistent failures
  • Observability dashboards: run status, per-sample progress, queue depth, cost-per-sample, and compute utilisation in real time
  • Full audit trail per pipeline run: tool versions, parameter sets, reference genome build, input checksums, output manifests - immutable and query-able
  • HIPAA-compliant data handling: encrypted compute environments, VPC isolation, IAM enforcement, and PHI access logging across all pipeline stages

Ready to build pipelines that run without you?

Talk to a pipeline engineering specialist about your stack, scale, and assay types.

Schedule a Call →
Who We Work With

Built for Teams at Every Stage of the Genomics Journey

Our NGS pipeline development services are trusted by organizations across the genomics spectrum.

Clinical & Reference Labs

CAP-accredited and CLIA-certified labs needing pipelines that meet regulatory requirements, pass inspection, and produce auditable outputs.

  • Somatic oncology panels
  • Hereditary disease WES/WGS
  • HIPAA-compliant infrastructure
  • TAT reduction engineering

Research Institutions & Biobanks

Population cohort studies and biobank programmes needing pipelines that process thousands of samples without manual oversight across multi-site environments.

  • Cohort-scale WGS pipelines
  • Multi-site harmonised analysis
  • Data governance & provenance
  • HPC + cloud hybrid infra

Genomics Startups & Scale-ups

Early-stage companies needing a production-grade pipeline platform without the time or headcount to build one in-house. We move fast and build right the first time.

  • First pipeline build
  • Outsourced pipeline engineering
  • Investor-ready architecture
  • Flexible engagement models
Platforms

Purpose-Built Platforms for Your Pipeline Outputs

A well-engineered pipeline is only as valuable as what happens after the variant calls. These NonStop platforms are built to receive, interpret, and act on your pipeline outputs:

Bioinformatics Pipeline Platform

The managed execution layer — auto-scaling, fully observable, with built-in cost tracking and failure recovery.

View Platform →

AI Genomic Data & Analytics Platform

AI-driven variant classification, VUS re-analysis, and cohort-level querying — sitting directly on your pipeline output layer.

View Platform →

Clinical Genomics Platform

Full clinical workflow — pipeline execution through ACMG classification, report generation, and delivery to providers and patients.

View Platform →
Build With a Partner, Not Just a Vendor

Frequently Asked Questions

What is included in NonStop's NGS pipeline development services?

Our NGS pipeline development services cover the complete pipeline lifecycle: architecture design, workflow framework selection (Nextflow, WDL, or Snakemake), containerised pipeline development, variant calling (germline, somatic, CNV, SV), annotation, QC, and observability engineering - deployed to your cloud (AWS, GCP, Azure) or HPC environment. Every engagement includes validation documentation and a structured handover to your internal team.A production-ready clinical bioinformatics pipeline must be reproducible across runs, scalable for clinical sample volumes, auditable for regulatory compliance, and integrated with clinical systems such as LIMS and reporting platforms.

How do you reduce turnaround time (TAT) in genetic testing through software?

TAT reduction comes from eliminating manual handoffs, parallelising execution, and automating failure recovery. Our pipeline engineering typically reduces TAT by 60–80% compared to manually managed systems - through auto-scaling compute allocation, automated QC and pass/fail gating, direct sequencer-to-pipeline triggers, and automated output delivery to LIMS and reporting systems. We document baseline versus post-implementation TAT for every engagement.

Do you build HIPAA-compliant bioinformatics pipelines for clinical environments?

Yes. Every pipeline we deliver for clinical lab environments is architected for HIPAA compliance. This includes encrypted compute environments (at rest and in transit), VPC network isolation, role-based access controls via IAM, PHI access logging, and immutable audit trails. We deliver compliance control documentation as part of the standard pipeline delivery package, including BAA support for cloud vendor relationships.

When should a clinical lab outsource bioinformatics pipeline development?

We deploy to AWS (Batch, EKS, Genomics CLI, S3), GCP (Life Sciences API, GKE, Cloud Storage), and Azure (Batch, AKS, Blob Storage). We also support hybrid architectures that combine on-premises HPC (SLURM, LSF) with cloud-burst compute. Our cloud-native pipeline platforms are designed to leverage spot and preemptible instances for cost optimisation while maintaining reliability through automatic retry on instance reclamation.

Ready to Build Pipelines That Run Without You?

Tell us your assay types, your data volumes, and your biggest operational headache. We will come back with a scoped approach and a realistic timeline.

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