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wellwellwell

Tools for processing 96-well plates

https://github.com/utrechtuniversity/wellwellwell

Science Score: 44.0%

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

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
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    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary

Keywords

96-well-plate polars python rlu ros-assay
Last synced: 6 months ago · JSON representation ·

Repository

Tools for processing 96-well plates

Basic Info
  • Host: GitHub
  • Owner: UtrechtUniversity
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 6.14 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 6
  • Releases: 0
Topics
96-well-plate polars python rlu ros-assay
Created almost 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

readme.md

Wellwellwelcome! In this repository you will find tools for processing 96-well plate data. There are 4 distinct parts to this toolset:

  • data ingest: reading in raw data formats produced by various 96-well plate processors
  • normalization: pre-processing of data to make it compatible for adequate analysis
  • statistical analysis: computation of valuable statistics
  • plots: different plots for visualizing statistics

If this software does not do what you need it to do, please make an issue! I am looking for:

  • examples of plots and graphs that you would like to recreate
  • datasets that you would like to process
  • statistical tests that you would like to run
  • normalization methods you have seen uin the wild and would like to have critically evaluated

Technologies

  • polars is used for data transformations; it is a modern alternative to pandas and is very fast and efficient for both big and small datasets
  • seaborn is used for plots; it is a very low level layer over matplotlib allowing for both a good degree of readability and ergonomics in creating visualizations

Quickstart

There are 2 ways to get started with this project and depending on your intentions, you should pick whichever suits you best.

Use the codespace quickstart if:

  • you just want to get to the data analysis
  • you don't have a lot of python experience
  • you are not excited by the prospect into running into issues with installing stuff
  • you want an easily reproducible pipeline that you can share with peers and stakeholders

Use the developer quickstart if:

  • pip install is not gibberish to you
  • you intend to use this as only a small part of a much mroe complex pipeline

Codespace quickstart

TODO: instructions

Video Tutorial

uu-rlu-space

Developer quickstart

  1. clone the repository
  2. install poetry using pipx (python3 -m pipx install poetry)
  3. poetry install in the root directory

Examples

Owner

  • Name: Utrecht University
  • Login: UtrechtUniversity
  • Kind: organization
  • Email: info.rdm@uu.nl
  • Location: Utrecht, The Netherlands

The central place for managing code and software for Utrecht University researchers and employees

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: wellwellwell
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Donatas
    family-names: Rasiukevicius
    email: donatas@rasiukevicius.dev
    orcid: 'https://orcid.org/0009-0006-3103-0108'
repository-code: 'https://github.com/UtrechtUniversity/wellwellwell'
abstract: Toolkit for processing data from 96 well plates
keywords:
  - ROS analysis
  - 96 well plates
license: GPL-3.0

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 19
  • Total Committers: 1
  • Avg Commits per committer: 19.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Donatas Rasiukevičius d****s@u****l 19
Committer Domains (Top 20 + Academic)
uu.nl: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 10
  • Total pull requests: 4
  • Average time to close issues: 14 days
  • Average time to close pull requests: less than a minute
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 3
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • fliepeltje (9)
Pull Request Authors
  • dependabot[bot] (3)
Top Labels
Issue Labels
enhancement (5) bug (1) documentation (1)
Pull Request Labels
dependencies (3)