Metadata-Version: 2.4
Name: spectrum_io
Version: 0.9.0
Summary: IO related functionalities for oktoberfest.
License-Expression: MIT
License-File: LICENSE
Author: Wilhelmlab at Technical University of Munich
Requires-Python: >=3.10,<3.14
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Dist: alphatims (>=1.0.8,<2.0.0)
Requires-Dist: h5py (>=3.1.0,<4.0.0)
Requires-Dist: numpy (>=2.0)
Requires-Dist: pandas (>=1.3,<3.0)
Requires-Dist: pyarrow (>=16.0.0)
Requires-Dist: pymzml (>=2.5.0,<3.0.0)
Requires-Dist: pyopenms (>=3.0.0)
Requires-Dist: pyteomics[xml] (>=4.3.3,<5.0.0)
Requires-Dist: rich (>=10.3.0)
Requires-Dist: scipy (>=1.0.0)
Requires-Dist: sortedcontainers (>=2.4.0,<3.0.0)
Requires-Dist: spectrum-fundamentals (>=0.9.0)
Project-URL: Documentation, https://spectrum-io.readthedocs.io
Project-URL: Homepage, https://github.com/wilhelm-lab/spectrum_io
Project-URL: Repository, https://github.com/wilhelm-lab/spectrum_io
Description-Content-Type: text/x-rst

Spectrum IO: File / Data Conversion for Mass Spec data within the Oktoberfest ecosystem
=======================================================================================

|PyPI| |Python Version| |License| |Read the Docs| |CI| |Codecov| |pre-commit| |Ruff|

.. |PyPI| image:: https://img.shields.io/pypi/v/spectrum_io.svg
   :target: https://pypi.org/project/spectrum_io/
   :alt: PyPI
.. |Python Version| image:: https://img.shields.io/pypi/pyversions/spectrum_io
   :target: https://pypi.org/project/spectrum_io
   :alt: Python Version
.. |License| image:: https://img.shields.io/github/license/wilhelm-lab/spectrum_io
   :target: https://opensource.org/licenses/MIT
   :alt: License
.. |Read the Docs| image:: https://img.shields.io/readthedocs/spectrum_io/latest.svg?label=Read%20the%20Docs
   :target: https://spectrum-io.readthedocs.io/
   :alt: Read the documentation at https://spectrum-io.readthedocs.io/
.. |CI| image:: https://github.com/wilhelm-lab/spectrum_io/workflows/CI/badge.svg
   :target: https://github.com/wilhelm-lab/spectrum_io/actions?workflow=CI
   :alt: CI Status
.. |Codecov| image:: https://codecov.io/gh/wilhelm-lab/spectrum_io/branch/main/graph/badge.svg
   :target: https://codecov.io/gh/wilhelm-lab/spectrum_io
   :alt: Codecov
.. |pre-commit| image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white
   :target: https://github.com/pre-commit/pre-commit
   :alt: pre-commit
.. |Ruff| image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
   :target: https://github.com/astral-sh/ruff
   :alt: Ruff

spectrum_io is a package primarily developed for usage within the rescoring and spectral library generation pipeline oktoberfest (https://github.com/wilhelm-lab/oktoberfest).

It provides the following functionalities:
 -   read search results from different search engines (MaxQuant, MSFragger, Sage, Xisearch) or a generic csv format and transform them to the internal format for rescoring with oktoberfest
 -   extraction of MS2 level spectra from .RAW files and conversion to to mzML for rescoring with oktoberfest
 -   spectra extraction from .d folders, conversion to .hdf5 format, and aggregation to MS2 level with metadata from a MaxQuant search for timsTOF rescoring with oktoberfest
 -   in-silico digestion of a fasta file with various configuration options (protease, missed cleavages, length of peptides, fragmentation, ...) for spectral library generation with oktoberfest
 -   write spectral libraries in dlib, msp, or spectronaut(csv) format
 -   parquet file creation for peptide prediction model development and refinement within DLOmix

Documentation
==============

The official documentation is available at https://spectrum-io.readthedocs.io/

How to Cite
===========

Please always cite the main publication:

Oktoberfest: Picciani M, Gabriel W, Giurcoiu VG *et al.* (2023), *Oktoberfest: Open-source spectral library generation and rescoring pipeline based on Prosit*, `Proteomics <https://doi.org/10.1002/pmic.202300112>`_

