Crow is no longer maintained - I am leaving the code up in case anyone find it useful for their lab or any new projects!
Crow can be installed from the python package index (PyPi) with the following command:
pip install CrowHTE
Crow can then be started by typing crow in the command line.
A step-by-step setup tutorial, including how to set up a python environment and access this repository, is available here.
To configure Crow to work for your instruments, modify config.yaml to work for your local installation. Data is retrieved by parsing XML files output by the software on the High Throughput Experimentation instrument. For example, our setup uses an Agilent GC and their software to run experiments and calculate eluate peak areas. Again, for an in-depth setup tutorial, see here.
Crow has three tabs: Pre-Pull, Pull, and Present. Pre-Pull identifies all peaks (and their areas) present in a given data set and generates a histogram of elution times. This is intended to help the user decide on a retention time (and small tolerance window) for each eluate to be pulled from the instrument data. With the help of Pre-Pull, Pull enables users to rapidly retrieve the peak areas for large datasets and export them to an Excel file (.csv) for easy manipulation. Present takes Excel files including only the data to be placed in the pie charts, which can then be filtered in a variety of ways to better represent multivariate data.
The above information is also explained in the video tutorial below: Crow SOP
If you need help with setting up Crow, finding out how to retrieve data from your HTE instrument, or you find this program at all helpful, send me a message.
To contribute to project, report or a bug, or request a new feature, open a pull request using one of the provided templates.