Skip to main content

Convert multiple files into quantms.io format

Project description

quantms.io

Python application

quantms is a nf-core pipeline for the analysis of quantitative proteomics data. The pipeline is based on the OpenMS framework and DIA-NN; and it is designed to analyze large scale experiments. the main outputs of quantms tools are the following:

  • mzTab files with the identification and quantification information.
  • MSstats input file with the peptide quantification values needed for the MSstats analysis.
  • MSstats output file with the differential expression values for each protein.
  • The input SDRF of the pipeline if available.

Here, we aim to formalize and develop a more standardized format that enables better representation of the identification and quantification results but also enables new and novel use cases for proteomics data analysis:

  • Fast and easy visualization of the identification and quantification results.
  • Easy integration with other omics data.
  • Easy integration with sample metadata.
  • AI/ML model development based on identification and quantification results.

Note: We are not trying to replace the mzTab format, but to provide a new format that enables AI-related use cases. Most of the features of the mzTab format will be included in the new format.

Data model

The GitHub repository aims to provide multiple formats for serialization of the data model, including:

  • Tab-delimited format similar to mzTab.
  • JSON format to enable integration with other bioinformatics resources.
  • Parquet format to enable integration with big data frameworks and large-scale data integration.

How to contribute

External contributors, researchers and the proteomics community are more than welcome to contribute to this project.

Contribute with the specification: you can contribute to the specification with ideas or refinements by adding an issue into the issue tracker or performing a PR.

Core contributors and collaborators

The project is run by different groups:

  • Yasset Perez-Riverol (PRIDE Team, European Bioinformatics Institute - EMBL-EBI, U.K.)

IMPORTANT: If you contribute with the following specification, please make sure to add your name to the list of contributors.

Code of Conduct

As part of our efforts toward delivering open and inclusive science, we follow the Contributor Covenant Code of Conduct for Open Source Projects.

How to cite

Copyright notice

This information is free; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.

This information is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this work; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantmsio-0.0.3.tar.gz (445.1 kB view details)

Uploaded Source

Built Distribution

quantmsio-0.0.3-py3-none-any.whl (462.5 kB view details)

Uploaded Python 3

File details

Details for the file quantmsio-0.0.3.tar.gz.

File metadata

  • Download URL: quantmsio-0.0.3.tar.gz
  • Upload date:
  • Size: 445.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.19

File hashes

Hashes for quantmsio-0.0.3.tar.gz
Algorithm Hash digest
SHA256 1f1884d0f40673fc68a2191bd59fbf8c20b2ace90035778dae2b9e81ff106713
MD5 64a576b5bff43d9b7ee59989821e122c
BLAKE2b-256 b523376a1292f7345f065258b240118e0b7db22945415bc5c5f9475bac59956d

See more details on using hashes here.

File details

Details for the file quantmsio-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: quantmsio-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 462.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.19

File hashes

Hashes for quantmsio-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 31f6da963bfb2e56d667bdc41174ecdf855786746caedbc63ec8a7f7400e7e1c
MD5 01a45f989a6fe5aa9d1febc516ed6577
BLAKE2b-256 de6e9047503c947c651f95f2467535d23b077e52071fd0a01ffdcdf2da47f7f0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page