Bioinformatics Solutions on AWS

Bioinformatics analysis is complicated. There is no one size fits all solution, and most infrastructures are created from many different components.

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Data Visualization

Deploy load balanced, fault tolerant RShiny and Dash applications on AWS. Each deployment is completely customizable and can include additional file systems, databases, and compute clusters.

SLURM HPC Clusters

Explore your large datasets on your own HPC Cluster on AWS. Avoid having to manually bring instances up and down with on demand by leveraging the scheduler to do the work for you. 

Data Science Pipelines

Design complex data science pipelines with the help of Apache Airflow. Generate QC reports, label images, train models, and execute computationally intensive workloads with the help of AWSBatch or HPC. 

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If you have any questions you can email me directly at

What You Get

You will always receive:

  • All the configuration written as code using either Terraform or CloudFormation. This code is completely yours and free of any intellectual property. You can use and reuse as you like.
  • Scripts to build, test and deploy that can be integrated with any CI / CD service.
  • Dockerfile and docker images that includes all the CLIs needed to deploy your infrastructure. No need to clobber your laptop!
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Why Work With Me?

Over the course of my career, I have earned a robust reputation for outstanding genomics and bioinformatics DevOps, and I am known for my ability to design and integrate innovative, flexible infrastructures, leveraging in-depth client and business consultation to uncover critical, unique program needs. Throughout the years I’ve seen datasets grow in size and complexity (who remembers microarrays?) and worked with researchers to develop analysis infrastructure to accommodate the ever-growing demand for more number crunching. 

I have consulted with the Bioinformatics Contract Research Organization (CRO) and BitBio to design and deploy a major manual-labor saving HPC cluster with integrated SLURM scheduler and user / software stacks, and elastic computational infrastructure for genomics analysis, empowering a greater focus on high-priority projects and activities.

I also designed and deployed complex data visualization applications on AWS such as NASQAR.  I am both a contributor and core team member of Bioconda as well as a contributor to the Conda Ecosystem and EasyBuild

Let's Deploy!

Prefer to DIY

That's great! I have oodles of material for people who want to deploy their own resources.

Deploy all the things!

Here are some blog posts that I hope find helpful! If you have any requests for tutorials please don't hesitate to reach out to me at

Data Science and Machine Learning Pipelines

Data Visualization Applications AWS