This cloud-based learning module is specialized for pathway analyses using omics datasets to discover consistent biological mechanism behind a condition. The content will be arranged in five sub-modules which allows us to:

  1. Download and process data from public repositories

  2. Perform differential analysis

  3. Perform pathway analysis using different methods that seek to answer different research hypotheses

  4. Perform meta-analysis and combine methods and datasets to find consensus results

  5. Interactively explore significantly impacted pathways across multiple analyses, and browsing relationships between pathways and genes.


Each learning sub-modules will be organized in a R Jupyter notebook to help the participants familiarize themselves with the cloud computing in the specific context of running bioinformatics workflows. Each notebook will include step-by-step hand-one practice with R command line to install necessary tools, obtain data, perform analysis, visualize and interpret the results.

This learning module does require any computational hardware and local environment setting from users. However, users need to have Google email account, sufficient internet access, and a stardard web-browser (e.g. Chrome, Edge, Firefox etc., Chrome browser is recommended) to create a cloud virtual machine for analysis.

The notebooks using in this cloud-based learning module are mainly designed to use with Google Cloud Platform (GCP) but not limited to Amazon Web Service, and Microsoft Azure. The detailed instruction of setting a Google Cloud virtual machine with our Github is given in the Getting Started below.

Sub-module 01

Sub-module 03

Sub-module 04

Sub-module 05