Paper Info
Title
proFIA: a data preprocessing workflow for flow injection analysis coupled to high-resolution mass spectrometry.
Abstract
Motivation: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. Results: We thus developed the proFIA package, which implements a suite of innovative algorithms to preprocess FIA-HRMS raw files, and generates the table of peak intensities. The workflow consists of 3 steps: (i) noise estimation, peak detection and quantification, (ii) peak grouping across samples and (iii) missing value imputation. In addition, we have implemented a new indicator to quantify the potential alteration of the feature peak shape due to matrix effect. The preprocessing is fast (less than 15 s per file), and the value of the main parameters (ppm and dmz) can be easily inferred from the mass resolution of the instrument. Application to two metabolomics datasets (including spiked serum samples) showed high precision (96%) and recall (98%) compared with manual integration. These results demonstrate that proFIA achieves very efficient and robust detection and quantification of FIA-HRMS data, and opens new opportunities for high-throughput phenotyping.
Year
DOI
Venue
2017
10.1093/bioinformatics/btx458
BIOINFORMATICS
Field
DocType
Volume
Resolution (mass spectrometry),Matrix (chemical analysis),Data mining,Computer science,Bioconductor,Data pre-processing,Preprocessor,Software,Imputation (statistics),Workflow
Journal
33
Issue
ISSN
Citations 
23
1367-4803
0
PageRank 
References 
Authors
0.34
6
6
Name
Order
Citations
PageRank
Alexis Delabrière100.34
Ulli M Hohenester200.34
Benoit Colsch301.01
Christophe Junot400.34
François Fenaille500.34
Etienne A Thévenot6131.50