Team Teri

How this Repo is Organized

This Repo contains my own 'study notes' as I learn genomic-scale cloud bioinformatics. It includes descriptions of common tools, platforms and summaries of my work with clients. I update this Repo frequently. It is organized via the folder structure shown below.

• 🗒️ Concepts and Terms (genomics files types, use cases, terminology and also whitepapers)
• 🔬 Lab Testing (Illumina and more)
• ⚒️ Genomic Tools (GATK, VariantSpark, HAIL and many more - this section updates OFTEN)
• 📦 Genomics Platforms (Terra.bio, Galaxy Project, IDSeq and others)
• ☁️ Public Cloud Genomics (Alibaba Cloud, AWS, Azure or GCP). The general approach is to implement a cloud-native Data Lake pattern for scalable genomic analysis. A conceptual rendering of this pattern is shown below.
• 📚 LLMs for Bioinformatics (Reading List). So many papers and tools are being published in this area. Here's what I am reading now.

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More Cloud/Genomics Reources

In addition to this Repo, I have a number of other Repos with cloud bioinformatics information. Also, I've included two of my favorite link aggregator resources here for additional learning.

My GitHub Open Source Courses

• :octocat: GENERAL CLOUD - my learn-cloud Repo - https://github.com/lynnlangit/learning-cloud
• :octocat: GCP - my gcp-for-bioinformatics open source course - https://github.com/lynnlangit/gcp-for-bioinformatics
• :octocat: AWS - my aws-for-bioinformatics open source course - https://github.com/lynnlangit/aws-for-bioinformatics
• :octocat: WDL language - my learn-wdl open source course - https://github.com/openwdl/learn-wdl

Repos with Links

• :octocat: awesome-bioinformatics(collection of links) - link with large number of curated links for learning about bioinformatics tools and topics
• :octocat: awesome-bioinformatics-benchmarks (collection of papers) - link links to published benchmark papers for bioinformatics

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Who is Teri?

Teri is the impetus for my movement into the world of genomic research. She was diagnosed with breast cancer in 2016. She survived, but suffered a long course of intense and painful treatment due in part to the lack of availability of personalized treatment options at the time of her diagnosis.