Peak Picking and Annotation of High Resolution Experiments

An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files.


peakPantheR

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peakPantheR

Package for Peak Picking and ANnoTation of High resolution Experiments in R, implemented in R and Shiny

Overview

peakPantheR implements functions to detect, integrate and report pre-defined features in MS files. It is designed for:

  • Real time feature detection and integration (see Real Time Annotation)
    • process multiple compounds in one file at a time
  • Post-acquisition feature detection, integration and reporting (see Parallel Annotation)
    • process multiple compounds in multiple files in parallel, store results in a single object

Installation

Install the development version of the package directly from GitHub with:

if(!require("devtools")) install.packages("devtools")
devtools::install_github("phenomecentre/peakPantheR")

If the dependencies mzR and MSnbase are not successfully installed, Bioconductor must be added to the default repositories with:

setRepositories(ind=1:2)

Usage

Both real time and parallel compound integration require a common set of information:

  • Path(s) to netCDF / mzML MS file(s)
  • An expected region of interest (RT / m/z window) for each compound.

Vignettes

More information is available in the following vignettes:

Copyright

peakPantheR is licensed under the GPLv3

As a summary, the GPLv3 license requires attribution, inclusion of copyright and license information, disclosure of source code and changes. Derivative work must be available under the same terms.

© National Phenome Centre (2018)

News

Reference manual

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install.packages("peakPantheR")

1.2.0 by Arnaud Wolfer, a year ago


Browse source code at https://github.com/cran/peakPantheR


Authors: Arnaud Wolfer [aut, cre] , Goncalo Correia [ctb] , Jake Pearce [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports foreach, doParallel, ggplot2, gridExtra, MSnbase, mzR, stringr, methods, XML, minpack.lm, scales

Suggests testthat, faahKO, knitr, rmarkdown, pander


See at CRAN