hplc-data-analysis 1.0.4

Tool for automatic analysis of multiple HPLC results

hplc_data_analysis

A Python tool to manage multiple HPLC qualitative tables and automatically split chemicals into functional groups.

An open-source Python tool that can automatically:

• handle multiple HPLC semi-quantitative data tables (obtained with different methods)
• duild a database of all identified compounds and their relevant properties using PubChemPy
• split each compound into its functional groups using a published fragmentation algorithm
• produce single file report, single replicate (intended as the sum of more methods applied to one vial), comprehensive multi-sample (average and deviation of replicates) reports and aggregated reports based on functional group mass fractions in the samples
• provides plotting capabilities

Naming convention for samples

To ensure the code handles replicates of the same sample correctly, names have to follow the convention: method_name-of-sample-with-dashes-only_replicatenumber (for now, method can either be 210 or 254, as the wavelenght analyzed using a UVvis detector

Examples that are correctly handled:

• 210_Bio-oil-foodwaste-250C_1
• 254_Bio-oil-foodwaste-250C_1
• 210_FW_2
• 254_FW_2

Examples of NON-ACCEPTABLE names are

• 210-bio_oil_1
• 254-FW1

Example

A comprehensive example is provided on the GitHub repository to show how inputs should be formatted. To test the module, install the hplc_data_analysis module, download the example folder given in the repository, and run the example_hplc_data_analysis.py. The folder_path needs to be set to where your data folder is.

The example code is shown here for convenience:

# example of hplc_data_analysis
import pathlib as plib
from hplc_data_analysis import Project
# this has to be changed to where the _example/data folder is
folder_path = plib.Path(plib.Path.cwd(), 'data')
# change this to folder_path = plib.Path(r"C:\Path\To\Your\Data") for your project
# class methods need to be called at the beginning to influence all instances
Project.set_folder_path(folder_path)
Project.set_plot_grid(False)
Project.set_plot_font('Sans')  # ('Times New Roman')

p = Project(rebuild_compounds_properties=False)
# %%
# p.create_compounds_properties()
p.create_files_replicates_samples()
a = p.files
aa = p.replicates[0]
aaa = p.replicates[1]
b = p.samples[0]
bb = p.samples_std[0]

p.create_all_statistics()
c, d = p.create_param_report()
p.save_files_report()
p.save_param_report()
p.save_param_aggrrep()
zz, zzstd = p.return_param_aggrrep(param='f_sample')

p.plot_ave_std(param='f_sample', aggr=True, min_y_thresh=0,
    color_palette='Set2')
p.plot_ave_std(min_y_thresh=200, legend_location='outside',
                only_samples_to_plot=['FW250C1h1', 'FWCP250C1h1'],
                )