Each of the following tutorials contains links to example datasets, instructions on how to use ExpressAnalyst, and images showing expected outcomes. Each tutorial can be completed in under one hour on a "normal" desktop or laptop computer.
  • Tutorial I: Overview of the main features and design of ExpressAnalyst
  • Tutorial II: How to analyze and visual exploration of one or more list(s) of genes
  • Tutorial III: How to perform gene expression data analysis, functional profiling and interactive visual exploration
  • Tutorial IV: How to perform meta-analysis and visualization of multiple gene expression data
  • Tutorial V: How to perform gene expression data analysis of a Seq2Fun counts table (non-model organisms)**
  • Tutorial VI: How to use the FASTQ module for raw reads processing. Use example data to practice uploading.
  • Please see our DockerHub page for tutorials and instructions on how to install and run the Docker implementation of raw data processing
** Note: tutorial V shows how to reproduce the salamander case study described in our manuscript
Dataset for the ExpressAnalyst Current Protocol
  • Data for Basic Protocol 1 - 4 (mouse_counts and mouse_meta in download link).
  • Data for Basic Protocol 6 (microarray and proteomics in download link).
  • Data for Basic Protocol 11 (FASTQ files in download link).
Dataset for the 2023 SOT CE Course
Download the counts matrix for the 2023 SOT CE course here. For details, see the original manuscript here.
System Requirements
ExpressAnalyst will work on any modern browser (ie. Chrome, Firefox, Safari). We suggest a 16-inch screen for best experience with the data visualization tools. The ExpressAnalyst SA Docker has been tested on Mac, Linux, and Windows operating systems. OS-specific instructions are given on the DockerHub page. We suggest at least 16GB RAM for local processing of FASTQ files with the Docker.