Read/write microplate and picklist data for lab automation
Project description
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Plateo (pronounced Plato, like the planet) is a Python library to assist in the planning, running and checking of laboratory experiments involving microplates.
It can be used to:
Read and write robotic protocols (picklists) in different formats to accomodate different liquid dispensers (Tecan EVO, Labcyte Echo).
Simulate liquid dispensing runs, taking into account the capacity and dead volume of each container, to predict the maps of future plates.
Parse plate data from common laboratory robots (for kinetic experiments, fragment analysis, qPCR, etc.)
Export plate information in various formats (graphics, spreadsheets, HTML, JSON, etc.).
Work in progress - contribute !
Plateo is an open-source software originally written at the Edinburgh Genome Foundry (an academic platform) by Zulko and released on Github under the MIT licence (¢ Edinburgh Genome Foundry).
It was released in the hope that it will be as useful for other automated labs as it is for use, but keep in mind that it is still under development, the features and docs will get better.
Plateo aims at collecting parsers and export routines to speak to any kind of automated equipment. If you have written parsers that don’t appear in Plateo, we are happy to hear about it. If you need help writing parsers for your favorite robot, we may be able to help too !
Installation
Plateo can be installed by unzipping the source code in one directory and using this command:
(sudo) python setup.py install
You can also install it directly from the Python Package Index with this command:
(sudo) pip install plateo
Code organization
Plate.py, Well.py and Picklist.py implement the central objects Plate, Well, and Picklist.
The containers folder contains specific classes of Plate and Well will predefined dimensions, capacity, dead volume, etc.
The parsers folder contains all methods to generate Plates or Picklists from machine files and data.
The exporters folder contains all methods to export plates in picklists in human- or machine-readable format.
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