Published September 7, 2023 | Version v1.0.0
Software Open

Taylor-CCB-Group/MDV: First Release

  • 1. Oxford University

Description

Multi-Dimensional Viewer (MDV) Release Notes

Version: 1.0.0
Release Date: 7th September 2023

Overview:

Multi-Dimensional Viewer (MDV) is a cutting-edge web-based application designed for the analysis, annotation, and sharing of multi-dimensional biological data from various modalities. Drawing inspiration from dc charts and crossfilter, MDV boasts performance even with datasets surpassing 10 million items, thanks to the use of web workers, shared array buffers, and native arrays.

Key Features:
  1. Variety of Interactive Charts/Widgets: Embed a large assortment of interactive charts and widgets in your analysis. These include:

    • Scatter plots (2D and 3D)
    • Box plots
    • Heat maps
    • Histograms
    • Pie charts
    • Violin plots
    • Annotation tools
    • Interactive spatial biology charts
  2. Storytelling with Data: Create multiple views or pages of data to weave a compelling narrative.

  3. Optimised for Multiple Screens: Pop out charts/widgets into separate windows to maximise the use of multiple screens.
  4. Support for Multiple Data Sources: Load multiple data sources (tables) and establish links between them.
  5. User-friendly Data Management: Add and/or modify data as per your requirements.
  6. Custom Data Loaders: Use a myriad of data sources (API calls, static files) by implementing custom data loaders.
Running On Local Machine:
  • Installation:

    1. Download and unzip the repository: MDV Repository
    2. Alternatively, clone it: git clone https://github.com/Taylor-CCB-Group/MDV.git
  • System Requirements:

    • A modern browser
    • Python (3.6 or above)
    • A mere 4GB of RAM suffices even for large datasets (~10,000,000 items) due to the lazy loading of raw bytes.
  • Displaying Example Data:

    1. Download the data: Example Data
    2. Navigate to the python directory: cd path/to/mdv/python
    3. Install the required Python packages: pip install -r requirements.txt
    4. Open a Python shell and create an MDV project from the downloaded folder. Display it in a browser. (Follow the provided instructions for this step.)
  • Running on a Server: Instructions provided for server setup and displaying an MDV project in a web page. Also, details on creating a static page for the project.

See the MDV GitHub page page for more detailed instructions and other options.

  • ### Feedback and Support: We value your feedback. If you have any questions, suggestions, or encounter any issues, please report them in Issues on GitHub.

Files

Taylor-CCB-Group/MDV-v1.0.0.zip

Files (13.0 MB)

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