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peakPantheR

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:

# Install devtools
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)

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Version

Install

install.packages('peakPantheR')

Monthly Downloads

6

Version

1.2.0

License

GPL-3

Maintainer

Arnaud Wolfer

Last Published

July 10th, 2018

Functions in peakPantheR (1.2.0)

generateIonChromatogram

Generate ion chromatogram from raw data points
peakFit,peakPantheRAnnotation-method

peakFit accessor
is.peakPantheR_curveFit

Check if object is of class peakPantheR_curveFit
outputAnnotationResult,peakPantheRAnnotation-method

Save to disk all annotation results as csv files Save to disk all annotation results as annotationName_ ... .csv files: compound metadata (cpdMetadata, cpdID, cpdName) and spectra metadata (spectraMetadata, acquisitionTime, TIC), summary of fit (ratio of peaks found: ratio_peaks_found, ratio of peaks filled: ratio_peaks_filled, mean ppm_error: ppm_error, mean rt_dev_sec: rt_dev_sec), and a file for each column of peakTables (with samples as rows and compounds as columns)
plotHistogram

Plot variable histogram and density
resetAnnotation,peakPantheRAnnotation-method

Reset a peakPantheRAnnotation and alter samples and compounds information Reset a peakPantheRAnnotation (remove results and set isAnnotated=FALSE). If a different number of samples (spectraPaths) or compounds (targetFeatTable) are passed, the object will be initialised to the new size. For input values left as NULL, the slots (filepath (from spectraPaths), ROI, cpdID, cpdName (from targetFeatTable), uROI, FIR, cpdMetadata, spectraMetadata, uROIExist, useUROI and useFIR) will be filled with values from previousAnnotation.
predictCurve

Predict curve values
plotPeakwidth

Plot peak value and peakwidth by acquisition time or in input order
plotEICFit

Plot samples raw data and detected feature for a single ROI
skewedGaussian_minpack.lm

Implementation of the Skewed Gaussian peak shape for use with minpack.lm
plotEICDetectedPeakwidth

Plot samples raw data and detected feature for a single ROI
isAnnotated,peakPantheRAnnotation-method

isAnnotated accessor
skewedGaussian_guess

Guess function for initial skewed gaussian parameters and bounds
spectraMetadata,peakPantheRAnnotation-method

spectraMetadata accessor
skewedGaussian_minpack.lm_objectiveFun

Skewed Gaussian minpack.lm objective function
peakTables,peakPantheRAnnotation-method

peakTables accessor with cpdID and cpdName added back
peakPantheR_singleFileSearch

Search, integrate and report targeted features in a raw spectra
nbCompounds,peakPantheRAnnotation-method

nbCompounds accessor established on cpdID
nbSamples,peakPantheRAnnotation-method

nbSamples accessor established on filepath
extractSignalRawData

Extract signal in a multiple defined mz rt window from a raw data file
peakPantheR

peakPantheR: A package for Peak Picking and ANnoTation of High resolution Experiments
outputAnnotationParamsCSV,peakPantheRAnnotation-method

Save annotation parameters as CSV Save annotation parameters (ROI, uROI and FIR) to disk as a CSV file for editing
outputAnnotationDiagnostic,peakPantheRAnnotation-method

Save to disk the annotation parameters as CSV and a diagnostic plot per fitted compound Save to disk the annotation parameters as CSV (as generated by outputAnnotationParamsCSV()) and a diagnostic plot per fitted compound (as generated by annotationDiagnosticMultiplot()) if savePlots is TRUE
[,peakPantheRAnnotation,ANY,ANY,ANY-method

extract parts of peakPantheRAnnotation class
uROI,peakPantheRAnnotation-method

uROI accessor returns targetFeatTable with cpdID, cpdName added
getTargetFeatureStatistic

Calculate chromatographic peak properties
integrateFIR

Integrate fallback integration regions
peakPantheR_parallelAnnotation

Search, integrate and report targeted features in a multiple spectra
peakPantheR_loadAnnotationParamsCSV

Load fit parameters from CSV
peakPantheRAnnotation

An S4 class to represent peakPantheR annotation results
saveSingleFileMultiEIC

Save to disk a plot of all ROI EIC and detected feature range
uROIExist,peakPantheRAnnotation-method

uROIExist accessor
useUROI,peakPantheRAnnotation-method

useUROI accessor
useFIR,peakPantheRAnnotation-method

useFIR accessor
skew_erf

Gaussian Error function
annotationTable,peakPantheRAnnotation-method

annotationTable accessor annotationTable returns a dataframe (row samples, col compounds) filled with a specific peakTable column
cpdID,peakPantheRAnnotation-method

cpdID accessor
cpdName,peakPantheRAnnotation-method

cpdName accessor
EICs,peakPantheRAnnotation-method

EICs accessor
cpdMetadata,peakPantheRAnnotation-method

cpdMetadata accessor
ROI,peakPantheRAnnotation-method

ROI accessor returns targetFeatTable with cpdID, cpdName added
FIR,peakPantheRAnnotation-method

FIR accessor returns targetFeatTable with cpdID, cpdName added
annotationDiagnosticPlots,peakPantheRAnnotation-method

Generate fit diagnostic plots Generate fit diagnostic plots for each ROI: EICFit the raw data and detected feature fit, rtPeakwidthVert detected peaks retention time apex and peakwidth (vertical and no run order), rtPeakwidthHorzRunOrder detected peaks retention time apex and peakwidth by run order, mzPeakwidthHorzRunOrder detected peaks m/z apex and peakwidth by run order, areaRunOrder detected peaks area by run order, rtHistogram histogram of detected peaks retention time, mzHistogram histogram of detected peaks m/z, areaHistogram histogram of detected peaks area.
TIC,peakPantheRAnnotation-method

TIC accessor
filename,peakPantheRAnnotation-method

filename accessor by spliting filepath
getAcquisitionDatemzML

Parse acquisition date from a mzML file
acquisitionTime,peakPantheRAnnotation-method

acquisitionTime accessor returns value as.POSIXct
filepath,peakPantheRAnnotation-method

filepath accessor
annotationDiagnosticMultiplot

Generate a multiplot of all diagnostic plots
dataPoints,peakPantheRAnnotation-method

dataPoints accessor
annotationParamsDiagnostic,peakPantheRAnnotation-method

Set uROI and FIR based on annotation results Set updated ROI (uROI) and Fallback Integration Regions (FIR) based on the annotation results. If the object is not annotated, it is returned untouched. ROI is not modified. If uROI exist they are left untouched, otherwise they are set as the minimum and maximum found peaks limits (+/-5% of ROI in retention time). If FIR are used they are left untouched, otherwise they are set as the median of the found limits (rtMin, rtMax, mzMin, mzMax).
findTargetFeatures

Find and integrate target features in each ROI
fitCurve

Curve fitting using minpack.lm