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KniMet: a pipeline for the processing of chromatography-mass spectrometry metabolomics data.

Published version
Peer-reviewed

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Authors

Hinz, Christine 
Hall, Zoe 
Santoru, Maria Laura 

Abstract

INTRODUCTION: Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow. OBJECTIVES: Merge in the same platform the steps required for metabolomics data processing. METHODS: KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform. RESULTS: The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation. CONCLUSION: KniMet provides the user with a local, modular and customizable workflow for the processing of both GC-MS and LC-MS open profiling data.

Description

Keywords

Data processing, GC–MS, LC–MS, Metabolomics

Journal Title

Metabolomics

Conference Name

Journal ISSN

1573-3882
1573-3890

Volume Title

14

Publisher

Springer Science and Business Media LLC
Sponsorship
Medical Research Council (MR/P011705/1)
Wellcome Trust (202952/B/16/Z)