This repository shows how to use ☁️Google Cloud Platform public cloud services to scale bioinformatics data analysis tasks using cloud best practices for GCP. This use cases featured as exampled are called any and all of the following: genomic-scale data workflows, pipelines, analysis or batch jobs.
This content is intended for researchers - in particular, this guide is for those who are NEW to working with GCP.
You have a number of options on how to use the materials provided in this course. A summary is shown below left.
This Repo includes content you can read, watch or run:
- 📗 READ - one page of this Repo (MD page)
- 📺 WATCH - linked YouTube screencasts
- 📙 TRY - Jupyter Notebook example
TRY - linked GitHub Repos
- 📘 EXPAND - linked (external) resources
- 🔍 SCAN - search a list in this Repo
⭐️Save Money run scaled analysis jobs exactly & only when you need to run them, Save Time use vendor-managed infrastructure & best-practice patterns for faster repeatable research
📗READ the FAQ for GCP bioinformatics for this Repo
📕READ Nature article: "Cloud computing for genomic data analysis and collaboration"
📗READ the top 4 most common use cases for using the public cloud for bioinformatics researchers
We love contributions! See this short style guide when making pull requests to this repo.