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
polars
is used for data transformations; it is a modern alternative to pandas and is very fast and efficient for both big and small datasetsseaborn
is used for plots; it is a very low level layer overmatplotlib
allowing for both a good degree of readability and ergonomics in creating visualizations
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
TODO: instructions
- clone the repository
- install poetry using
pipx
(python3 -m pipx install poetry
) poetry install
in the root directory