stdCurve  R Documentation 
stdCurve
, which was designed with mass spectrometry data in mind, fits
concentration and signal data to a standard curve and returns the calculated
betas, a plot of the standard curve, the data that were used to generate the
fitted line, and the original data that were used to generate the standard
curve.
stdCurve(
DF,
rawPeak,
rawIS,
normPeak,
nominal,
poly = "1st",
weights = NULL,
omit = NA,
IDcol = NA,
colorBy,
useNLS_outnames = TRUE
)
DF 
The input data.frame with columns containing the nominal analyte concentration and the instrument response 
rawPeak 
The unadjusted instrument response column. Ignore this if data are already normalized by internal standard. 
rawIS 
The internal standard column name. This is ignored if

normPeak 
The column containing instrument response normalized by internal standard. Use this if the data are peak heights or areas already divided by the IS peak height or area. 
nominal 
The column with the nominal concentrations or masses. 
poly 
Should the data be fit to a 1st or 2nd order polynomial? Options: "1st" or "2nd". 
weights 
Weighting scheme to use for the regression. User may supply a numeric vector of weights to use or choose from "1/x", "1/x^2", "1/y" or "1/y^2". If left as NULL, no weighting scheme will be used. Be careful that you don't have any infinite values or this will fail! 
omit 
An index of which, if any, samples to omit from the curve. These
samples will be depicted as red open circles in the graph but will not be
included in the regression. The red color for omitted points overrides any
other choices for 
IDcol 
Optional column with sample IDs 
colorBy 
What column to color the points by in the standard curve graph. If not set, all points will be black. 
useNLS_outnames 
TRUE or FALSE for whether the object "Fit" should be
the standard, list output from 
Output is a list of the following named objects:
The fitted parameters
A plot of the data and the fitted line
A data.frame of the points used for graphing the fitted line.
The original data with a column of the calculated concentration or mass as a percent of the nominal.
data(ExStdCurve)
# Using a peak ratio that's already been calculated
stdCurve(ExStdCurve,
normPeak = MET.peakarearatio,
nominal = MET.nominalmass,
poly = "2nd")
# Having 'stdCurve' calculate the peak ratio and making the fitted
# coefficients a data.frame rather than a list
stdCurve(ExStdCurve,
rawPeak = MET.area,
rawIS = d6MET.area,
nominal = MET.nominalmass,
poly = "2nd",
IDcol = SampleID,
useNLS_outnames = FALSE)
# Using weights in the nonlinear regression
stdCurve(ExStdCurve,
normPeak = MET.peakarearatio,
nominal = MET.nominalmass,
poly = "1st",
weights = "1/x")
# Omitting certain points from the regression but showing them on the graph
stdCurve(ExStdCurve,
normPeak = MET.peakarearatio,
nominal = MET.nominalmass,
poly = "2nd",
omit = which(ExStdCurve$MET.nominalmass > 10 &
ExStdCurve$MET.nominalmass < 20),
useNLS_outnames = FALSE)
# Coloring by some variable
stdCurve(ExStdCurve %>% dplyr::mutate(Group = c(rep("A", 5), rep("B", 6))),
normPeak = MET.peakarearatio,
nominal = MET.nominalmass,
colorBy = Group,
poly = "2nd")
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