peakPantheR_plotEICFit {peakPantheR} | R Documentation

## Plot samples raw data and detected feature for a single ROI

### Description

plot a ROI across multiple samples (x axis is RT, y axis is intensity). If curveFit is provided, the fitted curve for each sample is added.

### Usage

    peakPantheR_plotEICFit(
        ROIDataPointSampleList,
        curveFitSampleList = NULL,
        rtMin = NULL,
        rtMax = NULL,
        sampling = 250,
        sampleColour = NULL,
        verbose = TRUE
    )

### Arguments

`ROIDataPointSampleList` | (list) list of `data.frame` of raw data points for each sample (retention time 'rt', mass 'mz' and intensity 'int' (as column) of each raw data points (as row)).
`curveFitSampleList` | (list) NULL or a list of `peakPantheR_curveFit` (or NA) for each sample
`rtMin` | (float) NULL or vector of detected peak minimum retention time (in sec)
`rtMax` | (float) NULL or vector ofdetected peak maximum retention time (in sec)
`sampling` | (int) Number of points to employ when plotting fittedCurve
`sampleColour` | (str) NULL or vector colour for each sample (same length as `ROIDataPointSampleList`, `rtMin`, `rtMax`)
`verbose` | (bool) if TRUE message when NA scans are removed

### Value

Grob (ggplot object)

### Examples

    ## Input data
    # fake sample 1
    # ROI data points
    rt1             <- seq(990, 1010, by=20/250)
    mz1             <- rep(522., length(rt1))
    int1            <- (dnorm(rt1, mean=1000, sd=1.5) * 100) + 1
    tmp_DataPoints1 <- data.frame(rt=rt1, mz=mz1, int=int1)
    # fittedCurve
    fit1        <- list(amplitude=37.068916502809756, center=999.3734222573454,
                        sigma=0.58493182568124724, gamma=0.090582029276037035,
                        fitStatus=2, curveModel='skewedGaussian')
    class(fit1)     <- 'peakPantheR_curveFit'

    # fake sample 2
    # ROI data points
    rt2             <- seq(990, 1010, by=20/250)
    mz2             <- rep(522., length(rt2))
    int2            <- (dnorm(rt2, mean=1002, sd=1.5) * 100) + 1
    tmp_DataPoints2 <- data.frame(rt=rt2, mz=mz2, int=int2)
    # fittedCurve
    fit2        <- list(amplitude=37.073067416755556, center=1001.3736564832565,
                        sigma=0.58496485738212201, gamma=0.090553713725151905,
                        fitStatus=2, curveModel='skewedGaussian')
    class(fit2)     <- 'peakPantheR_curveFit'

    ## Plot features in 1 sample without colours
    peakPantheR_plotEICFit(ROIDataPointSampleList=list(tmp_DataPoints1),
                            curveFitSampleList=list(fit1),
                            rtMin=995., rtMax=1005.,
                            sampling=250, sampleColour=NULL, verbose=FALSE)

    ## Plot features in 2 samples with colours
    peakPantheR_plotEICFit(
                    ROIDataPointSampleList=list(tmp_DataPoints1,tmp_DataPoints2),
                    curveFitSampleList=list(fit1, fit2),
                    rtMin=c(995., 997.), rtMax=c(1005.,1007.),
                    sampling=250, sampleColour=c('blue', 'red'), verbose=FALSE)

[Package peakPantheR version 1.4.0 Index]