  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. Availability: The proFIA software (as well as the
plasFIA data set) is available as an R package on the Bioconductor repository
(http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main
Toolshed (https://toolshed.g2.bx.psu.edu/) and on the Workflow4Metabolomics
online infrastructure (http://workflow4metabolomics.org). Contacts:
<EMAIL_ADDRESS>and<EMAIL_ADDRESS>