The omniplate module allows the analysis and meta-analysis of data from plate readers. It is written in Python and described in Montaño et al., PLoS Comp Biol (2022).
Omniplate is most easily installed using pip:
pip install omniplate
but is also available at gitlab.
Both a walk-through tutorial, with some example data, and detailed documentation is available.
Omniplate requires an annotation file detailing what strains and media are in each well of the plate. We provide some example files and data from experiments run on a Tecan plate reader.
We use wells that contain only media to correct wells with both cells and media for the media's OD and fluorescence readings. In the annotation file, these media-only wells are denoted "null" to indicate no cells are present.
You can also load data that has already been parsed into columns, with headings time, well, OD, etc., and saved in a tsv or csv file. Please see the tutorial.
Omniplate was developed using funding from the Biotechnological and Biological Sciences Research Council, the Leverhulme Trust, and the Wellcome Trust.