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Accelerate PCR analysis and bioinformatics workflows

GenXFlo helps teams design and run production ready Nextflow pipelines. It keeps the flow simple for scientists and gives code level control to developers.

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PCR and genomics workflow illustration

About the project

GenXFlo is a SequoiaAT platform that turns PCR and sequencing steps into a clean visual pipeline. Each tool becomes a component. The system generates Nextflow code and Dockerfiles, then packages everything for a simple run. It supports teams across leading life sciences hubs in Boston and Cambridge, San Diego, the Bay Area, Raleigh Durham, New York City, Philadelphia, Chicago, Seattle, Houston, Indianapolis, and Austin.

  • Visual stitcher connects tools in the right order
  • Input, output, and reference paths are validated
  • Zero code start with developer friendly overrides

Who uses it

  • Research teams in Boston and Cambridge, San Diego, Bay Area, and Raleigh Durham running PCR and amplicon analysis
  • Bioinformatics groups standardizing lab to compute flow
  • Clinical labs and CROs seeking reproducible runs
SequoiaAT Life Sciences AI for data analysis Automation services

PCR workflow at a glance

Sample and metadata intake

Define paths for inputs and references. Keep naming consistent for smooth parsing.

Tool selection

Pick components for trimming, alignment, and variant calls. Required fields are flagged before submit.

Stitch and validate

Connect components in order. The canvas reflects flow. Errors are spotted early.

Code generation

GenXFlo builds Nextflow scripts and Dockerfiles. Everything ships in a single archive.

Execute

Extract and run make run. Docker pulls images and starts the process.

Results

Outputs land in the folder you set. Move straight to interpretation and reporting.

Why teams choose GenXFlo

80% less pipeline setup time
100% reproducible builds
0 data sent outside your network
15 minutes to first run

Reproducibility with Docker

Each component ships with a Dockerfile. Runs are consistent across laptops, clusters, and cloud.

Code control when needed

Scientists can start with defaults. Developers can tune arguments and extend steps.

Technology stack

  • Frontend: React
  • Backend: Spring Boot, Rust, Python
  • Data: PostgreSQL
  • Workflow: Nextflow, Make
  • Containers: Docker
Quality engineering Embedded expertise IoT solutions

Getting started

  1. Create a new pipeline in the app
  2. Set input, output, and references
  3. Select tools and connect steps
  4. Submit and download the archive
  5. Run make run after Docker setup
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Life sciences capability Clean tech work Mobile engineering Digital transformation
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