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Bioinformatics. 2017 Sep 14. doi: 10.1093/bioinformatics/btx582. [Epub ahead of print]

Ms2lda.org: web-based topic modelling for substructure discovery in mass spectrometry.

Author information

1
Glasgow Polyomics, University of Glasgow, Glasgow, United Kingdom. Contact:simon.rogers@glasgow.ac.uk.
2
Wellcome Centre for Molecular Parasitology, Glasgow, United Kingdom.
3
School of Computing Science, University of Glasgow, United Kingdom.

Abstract

Motivation:

We recently published MS2LDA, a method for the decomposition of sets of molecular fragment data derived from large metabolomics experiments. To make the method more widely available to the community, here we present ms2lda.org, a web application that allows users to upload their data, run MS2LDA analyses and explore the results through interactive visualisations.

Results:

Ms2lda.org takes tandem mass spectrometry data in many standard formats and allows the user to infer the sets of fragment and neutral loss features that co-occur together (Mass2Motifs). As an alternative workflow, the user can also decompose a dataset onto predefined Mass2Motifs. This is accomplished through the web interface or programmatically from our web service.

Availability and Implementation:

The website can be found at http://ms2lda.org , while the source code is available at https://github.com/sdrogers/ms2ldaviz under the MIT license.

Supplementary information:

Supplementary data are available at Bioinformatics online.

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