Our client was a biotechnology company developing precision gene‑editing therapies. Its research teams routinely perform high‑throughput editing experiments that generate large scale amplicon‑sequencing data per run.

Challenges

• Slow turnaround – Wet‑lab scientists waited days for bioinformatics teams to process raw reads and generate QC metrics.
• No continuous testing – Pipeline updates could silently introduce regressions, leading to failed analyses.
• Difficulty sharing results – Outputs were stored as flat files in S3 with no convenient, secure way to browse through results.

Delivery

Arrayo’s Approach: Arrayo clarified scientific and data requirements with researchers, then streamlined the existing workflow into a reproducible, containerized pipeline. The team wired this pipeline into a cloud‑native CI/CD path that runs miniature regression datasets on every commit and, on success, automatically publishes interactive HTML reports to an internal web gateway.

Solution and Implementation:

• Milestone 1 (Weeks 1‑2) – Discovery & Hardening
  • Audited the existing analysis scripts, containerized the genome‑editing workflow, and added rigorous parameter validation—eliminating the fragile‑analysis issue.
• Milestone 2 (Weeks 3‑4) – Cloud Infrastructure Baseline
  • Provisioned reproducible AWS resources (S3, ECR, Nextflow Tower workspace, IAM roles) via Terraform, enabling elastic compute and slashing run setup time.
• Milestone 3 (Weeks 5‑7) – Continuous Testing & Release Automation
  • Implemented a GitHub Actions → Nextflow Tower path that executes miniature “truth‑set” datasets on every pull request, posts status badges, and promotes container images only on success guaranteeing no surprise regressions.
• Milestone 4 (Weeks 8‑9) – Results Gateway & Enablement
  • Deployed a stateless NGINX gateway on AWS Fargate that serves S3‑hosted HTML reports and QC artefacts under secure, credential‑free HTTPS links.

Value

Results and Benefits:

• 80 % faster median turnaround (from ~48 h to <10 h) between sequencing run completion and QC report delivery.
• Zero surprise regressions because every code change is covered by on‑push tests against canonical datasets.
• Self‑service data access for >30 bench scientists via simple HTTPS links; no AWS credentials required.

Lessons Learned:

• Early investment in tiny “truth” datasets delivers robust testing in minutes and allows for catching edge‑cases quickly.
• Treating infrastructure as code (Terraform) simplified knowledge transfer and future environment cloning.
• Serverless components remove maintenance burden but demand thoughtful observability to debug cold‑start latency.

By coupling the bioinformatics workflow with cloud‑native automation and a lightweight results‑gateway, Arrayo delivered a reproducible, cost‑effective platform that turns raw sequencing reads into actionable editing‑outcome insights in hours instead of days. The solution empowered our client’s research teams to iterate faster and with greater confidence in their data quality.