Metadata-Version: 2.1
Name: pyhrms
Version: 0.5.1
Summary: A powerful GC/LC-HRMS data analysis tool
Home-page: https://github.com/WangRui5/PyHRMS.git
Author: Wang Rui
Author-email: wtrt7009@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
License-File: License.txt

  
  
PyHRMS: Tools For working with High Resolution Mass Spectrometry (HRMS) data in Environmental Science  
=====================================================================================================
  
  
PyHRMS is a python package for processing  high resolution Mass Spectrometry data coupled with gas
chromatogram (GC) or liquid chromatogram (LC).
  
It aims to provide user friendly tool to read,  process and visualize LC/GC-HRMS data for  scientist.
  
Contributers: Rui Wang  
======================
First release date: Nov.15.2021
  
Update
======
Jan.15.2023: pyhrms 0.5.01 new features:

    * optimize algorithm

    * add function to process SWATH data

Installation & major dependencies  
pyhrms can be installed and import as following:  

```
pip install pyhrms  
```

If you just want to update a new version, please update as following:

```
pip install pyhrms -U
```


pyhrms requires major dependencies: 
===================================

* numpy>=1.19.2

* pandas>1.3.3

* matplotlib>=3.3.2

* pymzml>=2.4.7

* scipy>=1.6.2

* molmass>=2021.6.18

* tqdm>=4.62.3

Features 
========
PyHRMS provides following functions:  

* Read raw LC/GC-HRMS data in mzML format;  
* Powerful and accurate peak picking function for LC/GC HRMS;  
* retention time (rt) and mass over Z stands for charge number of ions (m/z) will be aligned based on user defined error range.  
* Accurate function for comparing response between/among two or more samples;  
* Covert profile data to centroid  
* Parallel computing to improve efficiency;  
* Interactive visualizations of raw mzML data;  
* Supporting searching for Local database and massbank;  
* MS quality evaluation for ms data in profile.  
* Can process SWATH data.


Paper Published Utilizing PyHRMS
================================
* Jiang, X., Xue, Z., Chen, W., Xu, M., Liu, H., Liang, J., Zhang, L., Sun, Y., Liu, C., Yang, X., 2023. Biotransformation kinetics and pathways of typical synthetic progestins in soil microcosms. Journal of Hazardous Materials 446, 130684. https://doi.org/10.1016/j.jhazmat.2022.130684

* Liang, J., Wang, R., Liu, H., Xie, D., Tao, X., Zhou, J., Yin, H., Dang, Z., Lu, G., 2022. Unintentional formation of mixed chloro-bromo diphenyl ethers (PBCDEs), dibenzo-p-dioxins and dibenzofurans (PBCDD/Fs) from pyrolysis of polybrominated diphenyl ethers (PBDEs). Chemosphere 308, 136246. https://doi.org/10.1016/j.chemosphere.2022.136246

* Xia, D., Liu, H., Lu, Y., Liu, Y., Liang, J., Xie, D., Lu, G., Qiu, J., Wang, R., 2023. Utility of a non-target screening method to explore the chlorination of similar sulfonamide antibiotics: Pathways and N Cl intermediates. Science of The Total Environment 858, 160042. https://doi.org/10.1016/j.scitotenv.2022.160042

* Yang, X., Wang, R., He, Z., 2023. Abiotic transformation of synthetic progestins in representative soil mineral suspension. Journal of Environmental Science 127, 375-388. https://doi.org/10.1016/j.jes.2022.06.007



Licensing
=========

The package is open source and can be utilized under MIT license. Please find the detail in licence file.


