# mass2chem - low level utilities in interpreting mass spectrometry data
This package provides
- functions on handling chemical formulas
- formula based adduct calculation
- indexing and search functions on mass spec data
- libraries of common metabolites, contaminants, mass differences
- [to-do] functions of chemical similary, dataset similarity
## Related tools
- Generalized computing of isotopes and adducts: khipu (https://github.com/shuzhao-li-lab/khipu, https://pubs.acs.org/doi/10.1021/acs.analchem.2c05810)
- High-level metabolite functions and metabolic models: Json's Metabolite Services (JMS, https://github.com/shuzhao-li-lab/JMS)
- Metabolomics data processing: asari (https://github.com/shuzhao-li-lab/asari, https://www.nature.com/articles/s41467-023-39889-1)
- Python-Centric Pipeline for Metabolomics (https://github.com/shuzhao-li-lab/PythonCentricPipelineForMetabolomics)
- Common data models for metabolomics: metDataModel (https://github.com/shuzhao-li/metDataModel)
## Third party references:
https://github.com/opencobra/cobrapy/blob/devel/cobra/core/formula.py (using average molecular weight at the time of retrieval, not mass spec oriented)
https://github.com/domdfcoding/chemistry_tools
Pychemy (https://github.com/ginkgobioworks/pychemy).
Pychemy at this time isn't good fit for high-resolution metabolomics because its mass calculation is not of enough precision. E.g. in pychemy.adducts, it's wrong to use ('M+3H', 0.33, 1.0073),
because the computing/rounding error in 0.33 (correct is 1/3) is far too large for mass precision.
For high-resolution measurements, electrons should be considered too.
------------------------
Please do not hesitate to contact us via the GitHub issues.
Citation to come.
Raw data
{
"_id": null,
"home_page": "https://github.com/shuzhao-li/mass2chem",
"name": "mass2chem",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "chemistry,bioinformatics,mass spectrometry",
"author": "Shuzhao Li",
"author_email": "shuzhao.li@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/4c/b0/fc95c35b20424f9941476e6f4d0eacab1b0141065b2f090c24d3621fa68e/mass2chem-0.5.0.tar.gz",
"platform": null,
"description": "# mass2chem - low level utilities in interpreting mass spectrometry data\n\nThis package provides \n- functions on handling chemical formulas\n- formula based adduct calculation \n- indexing and search functions on mass spec data\n- libraries of common metabolites, contaminants, mass differences\n- [to-do] functions of chemical similary, dataset similarity\n\n## Related tools\n- Generalized computing of isotopes and adducts: khipu (https://github.com/shuzhao-li-lab/khipu, https://pubs.acs.org/doi/10.1021/acs.analchem.2c05810)\n\n- High-level metabolite functions and metabolic models: Json's Metabolite Services (JMS, https://github.com/shuzhao-li-lab/JMS)\n\n- Metabolomics data processing: asari (https://github.com/shuzhao-li-lab/asari, https://www.nature.com/articles/s41467-023-39889-1)\n\n- Python-Centric Pipeline for Metabolomics (https://github.com/shuzhao-li-lab/PythonCentricPipelineForMetabolomics)\n\n- Common data models for metabolomics: metDataModel (https://github.com/shuzhao-li/metDataModel)\n\n## Third party references:\n\nhttps://github.com/opencobra/cobrapy/blob/devel/cobra/core/formula.py (using average molecular weight at the time of retrieval, not mass spec oriented)\n\nhttps://github.com/domdfcoding/chemistry_tools\n\nPychemy (https://github.com/ginkgobioworks/pychemy). \nPychemy at this time isn't good fit for high-resolution metabolomics because its mass calculation is not of enough precision. E.g. in pychemy.adducts, it's wrong to use ('M+3H', 0.33, 1.0073),\nbecause the computing/rounding error in 0.33 (correct is 1/3) is far too large for mass precision.\nFor high-resolution measurements, electrons should be considered too.\n\n------------------------\nPlease do not hesitate to contact us via the GitHub issues.\n\nCitation to come.\n",
"bugtrack_url": null,
"license": "BSD",
"summary": "Common utilities for interpreting mass spectrometry data",
"version": "0.5.0",
"project_urls": {
"Homepage": "https://github.com/shuzhao-li/mass2chem"
},
"split_keywords": [
"chemistry",
"bioinformatics",
"mass spectrometry"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "8accff50dc8412431160f4000e9aa8cbbc7bf2c90915a7869201f7d73ddd04fe",
"md5": "95dad1a7c4b35e98390c1129b7cc4308",
"sha256": "9d8b5e19d54937195b846fe74093c1bb84b0ca4a1622d8931f20e56437af5978"
},
"downloads": -1,
"filename": "mass2chem-0.5.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "95dad1a7c4b35e98390c1129b7cc4308",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 273146,
"upload_time": "2024-02-06T22:59:52",
"upload_time_iso_8601": "2024-02-06T22:59:52.897593Z",
"url": "https://files.pythonhosted.org/packages/8a/cc/ff50dc8412431160f4000e9aa8cbbc7bf2c90915a7869201f7d73ddd04fe/mass2chem-0.5.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "4cb0fc95c35b20424f9941476e6f4d0eacab1b0141065b2f090c24d3621fa68e",
"md5": "fd12116d447568f88b136089f33a2c09",
"sha256": "0ef8a49e9ae7e39502edf881249bbdeb445225ae91e6b96da3828a3793f0f8f5"
},
"downloads": -1,
"filename": "mass2chem-0.5.0.tar.gz",
"has_sig": false,
"md5_digest": "fd12116d447568f88b136089f33a2c09",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 271987,
"upload_time": "2024-02-06T22:59:56",
"upload_time_iso_8601": "2024-02-06T22:59:56.014967Z",
"url": "https://files.pythonhosted.org/packages/4c/b0/fc95c35b20424f9941476e6f4d0eacab1b0141065b2f090c24d3621fa68e/mass2chem-0.5.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-02-06 22:59:56",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "shuzhao-li",
"github_project": "mass2chem",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"requirements": [],
"lcname": "mass2chem"
}
JSON
