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).

Installing

Omniplate is most easily installed using pip:

  pip install omniplate

but is also available at gitlab.

Using

Both a walk-through tutorial and detailed documentation is available.

Example data

Omniplate requires an annotation file detailing what strains and media are in each well of the plate. We provide an example file and the data from an experiment run on a Tecan plate reader in a format produced by the plate reader. Both are Microsoft Excel spreadsheets and are used in the tutorial.

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.

Acknowledgements

Omniplate was developed using funding from the Biotechnological and Biological Sciences Research Council, the Leverhulme Trust, and the Wellcome Trust.