Welcome to PyParse’s documentation!#
Authors: Joseph Mason, Francesco Rianjongdee, Harry Wilders, David Fallon
Description#
This script will read Liquid Chromatography Mass Spectrometry (LCMS) data in the Waters OpenLynx™ browser report (.rpt) file format or Shimadzu .daml file format, and assigns peaks to compounds specified in a .csv platemap. This assignment is then used to generate heatmaps and other visualisations to compare and contrast different LCMS runs. It was designed specifically for the analysis of data generated from high-throughput chemistry, and is suitable for reaction optimisations, parallel synthesis, library validation experiments and direct-to-biology.
Example Usage#
python PyParse.py example_rpt.rpt example_platemap.csv -o new_output_directory
python PyParse.py folder_containing_daml_files example_platemap.csv -o new_output_directory
License#
Apache 2.0
Copyright#
2023 GlaxoSmithKline Research & Development Limited
Indices and tables#
Contents#
- Installation and Run
- PyParse Outputs
- Using the Example Dataset
- Automatic Impurity Detection and Reporting
- Filtering by Retention Time
- Frequently Asked Questions
- Which UPLC/LCMS Vendors are Supported?
- Which plot type heatmap should I look at?
- What does “corrP/STD” actually mean?
- My plate design has deliberate gaps/empty wells in it - what do I do?
- I’d like to view the results in Excel/Spotfire/another program - how do I do this?
- The program didn’t find my product!!
- The output says “Peak overlap detected!” for my compound – what does this mean?
- Additional Parameters
- PyParse Function Detail
- Acquire Data from Water’s .rpt File
- Acquire Data from Shimadzu .daml Files