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dms-viz

dms-viz: Structure-informed visualiz ations for deep mutational scanning and other mutation-based datasets - Published in JOSS (2024)

https://github.com/dms-viz/dms-viz.github.io

Science Score: 93.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 5 DOI reference(s) in README and JOSS metadata
  • ✓
    Academic publication links
    Links to: biorxiv.org, joss.theoj.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software
Last synced: 6 months ago · JSON representation

Repository

Interactive tool for visualizing site-level data on a protein structure

Basic Info
  • Host: GitHub
  • Owner: dms-viz
  • License: mit
  • Language: JavaScript
  • Default Branch: main
  • Size: 52.6 MB
Statistics
  • Stars: 6
  • Watchers: 0
  • Forks: 1
  • Open Issues: 2
  • Releases: 22
Created over 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog Contributing License

README.md

dms-viz

dms-viz is an interactive web tool for visualizing site-level data on a protein structure with the capability of handling complex scenarios like multiple epitopes.

Check out the preprint here.

Usage

To use this tool, you'll need to put your data in the correct format. To do that, you can use the command line utility configuredmsviz.

Once you have your data in the correct format, you can upload it to dms-viz and start exploring!

Documentation

The details on how to use this tool are located here!

Please Cite Us

You can read the paper in JOSS. If you link to visualization with this tool, please cite us:

Hannon et al., (2024). dms-viz: Structure-informed visualizations for deep mutational scanning and other mutation-based datasets. Journal of Open Source Software, 9(99), 6129, https://doi.org/10.21105/joss.06129

Owner

  • Name: dms-viz
  • Login: dms-viz
  • Kind: organization

JOSS Publication

dms-viz: Structure-informed visualiz ations for deep mutational scanning and other mutation-based datasets
Published
July 17, 2024
DOI
Volume 9, Issue 99, Page 6129
Authors
William W. Hannon ORCID
Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington 98109, United States of America, Basic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States of America
Jesse D. Bloom ORCID
Basic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States of America, Department of Genome Sciences, University of Washington, Seattle, Washington 98109, United States of America, Howard Hughes Medical Institute, Seattle, Washington 98109, United States of America
Editor
Charlotte Soneson ORCID
Tags
javascript data visualization molecular biology protein biology deep mutational scanning
View PDF Review Thread Software Archive

GitHub Events

Total
  • Create event: 1
  • Release event: 1
  • Issues event: 5
  • Watch event: 1
  • Issue comment event: 6
  • Push event: 4
  • Pull request event: 2
  • Fork event: 1
Last Year
  • Create event: 1
  • Release event: 1
  • Issues event: 5
  • Watch event: 1
  • Issue comment event: 6
  • Push event: 4
  • Pull request event: 2
  • Fork event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 332
  • Total Committers: 1
  • Avg Commits per committer: 332.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 3
  • Committers: 1
  • Avg Commits per committer: 3.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Will Hannon h****w@g****m 332

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 78
  • Total pull requests: 21
  • Average time to close issues: 14 days
  • Average time to close pull requests: about 15 hours
  • Total issue authors: 7
  • Total pull request authors: 2
  • Average comments per issue: 0.73
  • Average comments per pull request: 0.0
  • Merged pull requests: 21
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 4
  • Pull requests: 1
  • Average time to close issues: 3 days
  • Average time to close pull requests: less than a minute
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • WillHannon-MCB (50)
  • Bernadetadad (9)
  • afrubin (7)
  • jbloom (5)
  • jkanche (1)
  • jgallowa07 (1)
  • Caleb-Carr (1)
Pull Request Authors
  • WillHannon-MCB (27)
  • csoneson (2)
Top Labels
Issue Labels
enhancement (24) bug (14) documentation (4) help wanted (1) question (1)
Pull Request Labels
enhancement (1)