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Bioinformatics. 2017 Dec 15;33(24):4007-4009. doi: 10.1093/bioinformatics/btx499.

PiMP my metabolome: an integrated, web-based tool for LC-MS metabolomics data.

Author information

1
Institute of Infection, Immunity and Inflammation, Glasgow Polyomics.
2
Centre for Cell Engineering.
3
School of Computing Science.
4
Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8QQ, UK.

Abstract

Summary:

The Polyomics integrated Metabolomics Pipeline (PiMP) fulfils an unmet need in metabolomics data analysis. PiMP offers automated and user-friendly analysis from mass spectrometry data acquisition to biological interpretation. Our key innovations are the Summary Page, which provides a simple overview of the experiment in the format of a scientific paper, containing the key findings of the experiment along with associated metadata; and the Metabolite Page, which provides a list of each metabolite accompanied by 'evidence cards', which provide a variety of criteria behind metabolite annotation including peak shapes, intensities in different sample groups and database information.

Availability and implementation:

PiMP is available at http://polyomics.mvls.gla.ac.uk, and access is freely available on request. 50 GB of space is allocated for data storage, with unrestricted number of samples and analyses per user. Source code is available at https://github.com/RonanDaly/pimp and licensed under the GPL.

Contact:

karl.burgess@glasgow.ac.uk.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
28961954
PMCID:
PMC5860087
DOI:
10.1093/bioinformatics/btx499
[Indexed for MEDLINE]
Free PMC Article

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