Package: proFIA
Type: Package
Title: Preprocessing of FIA-HRMS data
Version: 1.13.0
Date: 2016-06-06
Author: Alexis Delabriere and Etienne Thevenot.
Maintainer: Alexis Delabriere <alexis.delabriere@outlook.fr>
biocViews: MassSpectrometry, Metabolomics, Lipidomics, Preprocessing,
        PeakDetection, Proteomics
Depends: R (>= 2.5.0), xcms
Imports: stats, graphics, utils, grDevices, methods, pracma, Biobase,
        minpack.lm, BiocParallel, missForest, ropls
Suggests: BiocGenerics, plasFIA, knitr,
VignetteBuilder: knitr
Description: Flow Injection Analysis coupled to High-Resolution Mass
    Spectrometry is a promising approach for high-throughput
    metabolomics. FIA- HRMS data, however, cannot be pre-processed
    with current software tools which rely on liquid chromatography
    separation, or handle low resolution data only. Here we present
    the proFIA package, which implements a new methodology to
    pre-process FIA-HRMS raw data (netCDF, mzData, mzXML, and mzML)
    including noise modelling and injection peak reconstruction,
    and generate the peak table. The workflow includes noise
    modelling, band detection and filtering then signal matching
    and missing value imputation. The peak table can then be
    exported as a .tsv file for further analysis. Visualisations to
    assess the quality of the data and of the signal made are
    easely produced.
License: CeCILL
NeedsCompilation: yes
RoxygenNote: 6.0.1
Collate: 'Denoising.R' 'KNN_T.R' 'cWrapper.R' 'noiseEstimator.R'
        'classContainer.R' 'fastMatchPpm.R' 'findPeaksFIA.R'
        'methodsContainer.R' 'proFIA-package.R'
git_url: https://git.bioconductor.org/packages/proFIA
git_branch: master
git_last_commit: db7b31c
git_last_commit_date: 2019-10-29
Date/Publication: 2019-11-08
Packaged: 2019-11-09 03:57:29 UTC; biocbuild
Built: R 4.0.0; i386-w64-mingw32; 2019-11-09 10:27:27 UTC; windows
Archs: i386, x64
