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tracegroomer's Introduction

TraceGroomer

PyPI - Python Version bioconda package

TraceGroomer is a solution for formatting and normalising isotope-labeled (a.k.a Tracer) Metabolomics given file(s), to produce the tabular files which are ready for DIMet tool.

Not only one, but several input formats are accepted by TraceGroomer!: these input formats are described in detail (visit the Wiki link provided in our documentation section), e.g. IsoCor output files are currently supported.

TraceGroomer processes your data in seconds!

For any type of the supported inputs, TraceGroomer generates an independent file for each type of quantification: i) total metabolite abundances ii) Isotopologues iii) Isotopologues' proportions and iv) mean enrichment (a.k.a fractional contributions).

Advantages of using TraceGroomer for preparing your data for DIMet:

  • if only Isotopologues' absolute values are provided, TraceGroomer generates all the other quantifications automatically.
  • fast, automatic formatting is performed, as well as the normalization chosen by the user: whether by the amount of material and/or by an internal standard.
  • useful advanced options are offered (e.g. different modalities of normalization by the amount of material).

Note : TraceGroomer does not correct for naturally occurring isotopologues. Your data must be already processed by another software that performs such correction (e.g. IsoCor).

Important

When using TraceGroomer, please cite:

Galvis J, Guyon J, Dartigues B, Hecht H, Grüning B, Specque F, Soueidan H, Karkar S, Daubon T, Nikolski M. DIMet: An open-source tool for Differential analysis of targeted Isotope-labeled Metabolomics data. Bioinformatics 2024; 40(5) btae282. https://doi.org/10.1093/bioinformatics/btae282


Requirements

TraceGroomer requires Python 3.10+. Running in a virtual environment is highly recommended.

Install it via pip: pip install tracegroomer

Tracegroomer is also available as a conda package

Alternatively, if you are a developer, you can do a local install:

Local install of TraceGroomer (click to show/hide) For a local install, clone this repository, make sure you have activated your virtual environment with Python 3.10+ (source MY_VIRTUAL_ENV/bin/activate), with poetry installed.

Then install dependencies: locate yourself in TraceGroomer and run

poetry install

After this, the tool is ready to use:

python -m tracegroomer --help

Documentation

All the details about how to use TraceGroomer can be found on the dedicated Wiki page. This is where you will find the information of the supported formats, examples, and how to run TraceGroomer.

Getting help

For any information or help running TraceGroomer, you can get in touch with:


LICENSE MIT

Copyright (c) 2024

Johanna Galvis (1,2)    [email protected]
Benjamin Dartigues (2)	[email protected]
Slim Karkar (1,2)       [email protected]
Helge Hecht (3,5)       [email protected]
Bjorn Gruening (4,5)    [email protected]
Macha Nikolski (1,2)    [email protected]

(1) CNRS, IBGC - University of Bordeaux,
1, rue Camille Saint-Saens, Bordeaux, France

(2) CBiB - University of Bordeaux,
146, rue Leo Saignat, Bordeaux, France

(3) RECETOX
Faculty of Science, Masaryk University, Kotlářksá 2, 611 37 Brno, Czech Republic

(4) University of Freiburg,
Freiburg, Germany

(5) Galaxy Europe

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

tracegroomer's People

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tracegroomer's Issues

repeated code/functions

some functions are repetitive, e.g. those for stomping values: one for mean enrichment, one for isotopol proportions) --> one single function accepting both is enough; there are many other cases of repeated code

raw

delete raw subfolder requirement

PyPI record: missing fields; & find why Galaxy version fails to give output files

  • fix PyPI infos in .toml file: our PyPI record https://pypi.org/project/tracegroomer/ is NOT showing the link to github repo

  • solve: Galaxy version is not giving output when the normalizations (or the computation of metrics from absolute isotopologues) are performed: reason --> internally our tool assigns object frames names with suffix "_computed", and such names are used for output files in command line, but this perturbs the Galaxy version as it requires predictable names.

    • "auto-suit" the names of output files to presence/absence of quantification type, using the 'user defined' names, and combine with internal defaults for those 'not user defined'.
  • if possible: make the tool more robust: run even if user only provides total metabolite abundances

support dataMatrix + variableMetadata as input for TraceGroomer

Helge Hecht, Yann Guitton and Benjamin Dartigues agree on the need to add the choice of accepting the input in the form of .tsv files : variableMetadata and isotopologues_dataMatrix . Justifications: i) W4M wants, in a close future, to make these files, alongside the sample metadata, a rule for any metabolomics post-processing, ii) tools in W4M are evolving and new isotopologue correction tools that support this new format are in development by W4M or other Galaxy teams.

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