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ChAsE logo

ChAsE: Chromatin Analysis and Exploration Tool

ChAsE is a cross platform desktop application that provides an interactive graphical interface for analysis of epigenomic data.

Features include:

  • Exploration and visualization of the data using an interactive heat map and plot interface.
  • Clustering the data automatically or manually by sorting and brushing the heat map.
  • Set construction based on presence/absence of signal.
  • Ability to compare different clusterings via set operations.
  • Exporting results for downstream analysis or as high quality images for publications.

For more information, please check the official website.

Quick Start

Installation

This software requires Java 7 or greater. It is recommended that you get the latest version of Java SE.

  • Download and extract the latest binary distribution (v 1.1.2) if you don't want to build it yourself:

    • Windows: Double click Run_Windows.bat.
    • Mac: Right click Run_OSX.command and select Open. Confirm running the application.
    • Linux: Double click Run_Unix.sh.
    • Or, you may open a console and run the following in the command-line: java -jar chase.jar

Example Data

  • Example Data (full): Contains a GFF file for Refseq genes (mm9) and several WIG and BIGWIG files (ChIP-seq, RNA-seq and Bis-seq) which can be used to create a new workspace from scratch.
  • Example Data (small): Contains an example GFF file (mm9) and four small WIG files (ChIP-seq and RNA-seq) which can be used to create a new workspace from scratch.
  • Example Workspace: Contains the two pre-processed exmaple workspaces for the small and the full example data above, which can be readily opened using the [Open Existing Analysis] option.

Documentation

Video Walkthroughs


Full Video Walkthrough

Input: New Datasets
Input: Open Workspace
Input: Modify Parameters

Heatmap: Sorting
Heatmap: Navigation
Heatmap: Filtering

Method: K-means
Method: Cluster Comparison
Method: Signal Query

Credits

ChAsE is developed by Hamid Younesy under the supervision of Torsten Möller, and in close collaboration with Cydney Nielsen. Special thanks to Mohammad Karimi, Matthew Lorincz, Rebecca Cullum, Olivia Alder, Bradford Hoffman and Arthur Kirkpatrick for their feedback and help evaluating this tool.

Citation

Younesy H, Nielsen CB, Lorincz MC, Jones SJ, Karimi MM, Möller T. ChAsE: chromatin analysis and exploration tool. Bioinformatics. 2016 Jul 4;32(21):3324-6.