Time series data are often analysed for peak signals. Mass spectrometry data may contain flat top peaks due to technical limitations (i.e. detector saturation, DS). Flat top peaks can also be termed 'overloaded' signals. Extracting the peak height to infer signal intensity will obviously give wrong results for flat top peaks.
However, using the peak shape in the non-distorted fraction of the signal (intensity below DS), the true peak shape can be modeled mathematically. This modelling is the core task of CorrectOverloadedPeaks.
The R package accepts data in xcmsRaw and mzXML format as input. Overloaded signals are detected automatically and modified using an Gaussian or Isotopic-Ratio approach, QC plots are generated and corrected data are stored within the original xcmsRaw or mzXML respectively to allow further processing.
This way CorrectOverloadedPeaks can be incorporated in any metabolomics pipeline. Some
utility functions are additionally exported, i.e. read.mzData() and FitGaussPeak().
You can install the development version of CorrectOverloadedPeaks from GitHub with:
# install.packages("devtools")
devtools::install_github("janlisec/CorrectOverloadedPeaks")or install from CRAN instead.
This is a basic example, modelling a flat topped peak first and restoring the true shape assuming a Gaussian peak shape afterwards.
pk <- CorrectOverloadedPeaks::ModelGaussPeak(height=10^7, width=3, scan_rate=10, e=0, ds=8*10^6, base_line=10^2)
plot(pk, main="Gaussian peak of true intensity 10^7 but cutt off at 8*10^6")
idx <- pk[,"int"]>0.005 * max(pk[,"int"])
tmp <- CorrectOverloadedPeaks::FitGaussPeak(x=pk[idx,"rt"], y=pk[idx,"int"], silent=FALSE, xlab="RT", ylab="Intensity")Next, we load some real life measurement data and correct the two overloaded peaks contained.
data("mzXML_data", package = "CorrectOverloadedPeaks")
tmp <- CorrectOverloadedPeaks::CorrectOverloadedPeaks(data=mzXML_data, method="EMG", testing=TRUE)You might either read the Vignette describing the package functions in detail or read the publication which shows a evaluation of the performance of CorrectOverloadedPeaks on real data sets.