plot_quantlim: Plot of the curve used to calculate LOB and LOD

Description Usage Arguments Details Value Warning Author(s) References Examples

View source: R/plot_quantlim.R

Description

This function allows to plot the curve fit that is used to calculate the LOB and LOD with functions nonlinear_quantlim() and linear_quantlim(). The function outputs for each calibration curve, two pdf files each containg one plot. On the first, designated by *_overall.pdf, the entire concentration range is plotted. On the second plot, designated by *_zoom.pdf,, the concentration range between 0 and xlim_plot (if specified in the argument of the function) is plotted. When no xlim_plot value is specified, the region close to LOB and LOD is automatically plotted.

Usage

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plot_quantlim(spikeindata, quantlim_out, alpha, dir_output, xlim_plot)

Arguments

spikeindata

Data frame that contains the experimental spiked in data. This data frame should be identical to that used as input by function functions nonlinear_quantlim() or linear_quantlim(). The data frame has to contain the following columns : CONCENTRATION, INTENSITY (both of which are measurements from the spiked in experiment) and NAME which designates the name of the assay (e.g. the name of the peptide or protein)

quantlim_out

Data frame that was output by functions nonlinear_quantlim() or linear_quantlim(). It has to contain at least the following columns: i) CONCENTRATION: Concentration values at which the value of the fit is calculated ii) MEAN: The value of the curve fit iii) LOW: The value of the lower bound of the 95% prediction interval iv) UP: The value of the upper bound of the 95% prediction interval v) LOB: The value of the LOB (one column with identical values) vi) LOD: The value of the LOD (one column with identical values) vii) NAME: The name of the assay (identical to that provided in the input) viii) METHOD which is LINEAR or NONLINEAR

alpha

Probability level to estimate the LOB/LOD

dir_output

String containg the path of the directly where the pdf files of the plots should be output.

xlim_plot

Optional argument containing the maximum xaxis value of the zoom plot. When no value is specified, a suitable value close to LOD is automatically chosen.

Details

Value

Warning

This plotting function should ideally be used every time nonlinear_quantlim() or linear_quantlim() are called to visually ensure that the fits and data are accurate.

Author(s)

Cyril Galitzine, Olga Vitek.

Maintainer: Cyril Galitzine (cyrildgg@gmail.com), Meena Choi (mnchoi67@gmail.com)

References

C. Galitzine et al. "Nonlinear regression improves accuracy of characterization of multiplexed mass spectrometric assays" Mol Cell Proteomics, doi:10.1074/mcp.RA117.000322, 2018.

Examples

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# Consider data from a spiked-in contained in an example dataset. This dataset contains 
# a significant threshold at low concentrations that is not well captured by a linear fit.

head(SpikeInDataNonLinear)

## Not run: 
#Call function
nonlinear_quantlim_out <- nonlinear_quantlim(SpikeInDataNonLinear, alpha = 0.05)

plot_quantlim(spikeindata = SpikeInDataLinear, quantlim_out  = nonlinear_quantlim_out,
dir_output =  getwd(), alpha = 0.05)

## End(Not run)

MSstats documentation built on Feb. 28, 2021, 2:01 a.m.