Bespoke Engineering Studio
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Production-grade bioinformatics pipeline development — from raw sequencer output to clinically validated variant calls, engineered for reliability, scale, and long-term maintainability.
Why 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.
Scripts that work at 10 samples break at 200. No retry logic. No observability. One failed sample stalls the entire run.
Tool versions shift, reference builds diverge, containers go undocumented. Results vary between runs without an audit trail.
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?
Variant call files sit in object storage with no automated route to LIMS, reporting systems, or interpretation platforms.
Our Approach
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:
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.
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.
Benchmarked against NIST Genome in a Bottle and SEQC2 reference datasets. Analytical sensitivity, specificity, and concordance documented before production deployment.
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.
Capabilities
Every engagement is different — assay type, scale, compute environment, downstream system. Here is the full range of what our bioinformatics pipeline development practice covers.
We build and maintain WES and WGS pipelines from FASTQ ingestion through alignment, germline and somatic variant calling, annotation, and QC reporting.
Talk to a Pipeline Engineering Specialist →Somatic variant detection is technically demanding and clinically critical. We engineer somatic pipelines for comprehensive oncology and clinical coverage.
Talk to an Expert →All somatic pipelines are benchmarked against SEQC2 reference samples with documented sensitivity/specificity metrics before clinical deployment.
Transcriptomic workflows require a fundamentally different engineering approach from DNA-based pipelines. Our RNA-Seq development covers:
Schedule a Call →Clinical panel pipelines demand tighter requirements than research workflows — higher sensitivity thresholds, controlled QC, and regulatory traceability. We build for:
Let’s Talk →A variant call without annotation is a number without meaning. Our annotation stack covers:
Talk to an Expert →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.
Module-based pipeline design with nf-core standards, process-level containerisation, multi-profile config for local / HPC / AWS / GCP, and Seqera Platform integration for enterprise monitoring.
Cromwell and Terra execution backends, GATK Best Practices workflow adaptation, broad cloud genomics platform compatibility, and scatter-gather patterns for parallel sample processing.
Rule-based modular pipelines with Conda and Singularity environment management, SLURM and cloud backend integration — preferred for research-adjacent and mixed HPC/cloud environments.
If you have existing pipelines in bash scripts or a legacy workflow system, we assess, document, and migrate them to a maintainable production framework — without disrupting current runs.
A pipeline that fails silently is worse than one that fails loudly. Operational reliability is built into every pipeline we deliver:
EKS (AWS), GKE (GCP), or AKS (Azure) — auto-scaling node pools aligned to sample batch sizes.
Configurable retry logic — per-task retry counts, backoff strategies, and alerting on persistent failures.
Run status, per-sample progress, queue depth, cost-per-sample, and compute utilisation in real time.
Tool versions, parameter sets, reference genome build, input checksums, output manifests — immutable and query-able.
Encrypted compute environments, VPC isolation, IAM enforcement, and PHI access logging across all pipeline stages.
Who We Work With
Our NGS pipeline development services are trusted by organizations across the genomics spectrum.
CAP-accredited and CLIA-certified labs needing pipelines that meet regulatory requirements, pass inspection, and produce auditable outputs.
Population cohort studies and biobank programmes needing pipelines that process thousands of samples without manual oversight across multi-site environments.
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.
Platforms
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:
The managed execution layer — auto-scaling, fully observable, with built-in cost tracking and failure recovery.
View Platform →AI-driven variant classification, VUS re-analysis, and cohort-level querying — sitting directly on your pipeline output layer.
View Platform →Full clinical workflow — pipeline execution through ACMG classification, report generation, and delivery to providers and patients.
View Platform →FAQ
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.
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.
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.
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.
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.