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Metabolite Peak List Merge, Annotation & Polishing Tool: A user friendly, platform independent R tool to merge, annotate and polish metabolite-peak list data from LC-/GCMS runs

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Metapolish - the merging, annotation & polishing tool for metabolite peak list data

Scripting License: REASEARCH ONLY Current Version DOI

Metapolish is a R tool that allows easy data processing of common Liquid- and Gas Chromatography Mass Spectrometry (LC-/GCMS) raw peak data. The tool bridges the gap between the individual sample peak list outputs generated by MS-analysis software like Thermo Xcalibur-TraceFinder or Shimadzu GCMS solution and the standardised metabolite-concentration matrix input required by downstream metabolite analysis applications such as MetaboAnalyst.

The software is very easy to install, includes additional plotting and reporting functions and can be run on machines operating Windows, Mac OS or Linux in a reproducible and scalable manner. It reads in individual pre-processed LC-/GCMS data files containing compound-peak data of single samples, collects additional sample information regarding dry weight and creates normalised and polished Metabolite-Concentration Matrix outputs at different levels of condensation optimised for subseqeunt downstream analysis by MetaboAnalyst. Up to 198 input files of the type .pdf, .tsv, .csv, .txt or .xlsx can be processed at the same time.


Fig. 1: Schematic diagram displaying the individual files and steps of the tool

The tool can be operated following graphical user interphases (GUI) on top of R markdown scripts. The tool has been tested on both Mac and Windows operating systems, predominantly analysing GC/MS data obtained from different algae samples.

Key Features

  • Simplicity: The tool provides reproducible and scalable data analysis which can be executed across operating systems.
  • Integrated data extraction from .pdf and .xlsx files of common peak quantification tools: Starting from .pdf files the tool allows easy extraction of GC/MS summary data from common pre-processing tools such as Thermo Xcalibur-TraceFinder or Shimadzu GCMS solution.

Documentation:

Find the full documentation here: https://andreholzer.github.io/Metapolish/

Quick links:

Citation

If you use this pipeline for your analysis, please don't forget to cite:

DOI: … (coming soon, please get in contact before using the tool)

Developers

We would like to thank Monika Krolikowski for trailing the software and acknowledge Aom Buayam who contributed prototype files for parts of this tool.

License

RESEARCH PURPOSES ONLY!

For more details view full license agreement