Description Usage Format Details Examples
We normalize the intensity of the light peptides using that of the heavy peptides. This corrects any systematic errors that can occur during a run or across replicates. The calculation is greatly simplified by the use of the tidyr and dplyr packages. The area from all the different peptide fragments is first summed then log transformed. The median intensity of the reference heavy peptides medianlog2heavy is calculated. Their intensities should ideally remain constant across runs since the spiked concentration of the heavy peptide is constant. The difference between the median for all the heavy peptide spikes is calculated. It is then used to correct (i.e. to normalize) the intensity of the light peptides log2light to obtain the adjusted intensity log2light_norm. The intensity is finally converted back to original space. Details are available in vignette. The variables are as follows:
1 |
A data frame with 30 rows and 4 variables.
CONCENTRATION: Concentration values at which the value of the fit is calculated
MEAN: The value of the curve fit
LOW: The value of the lower bound of the 95\
UP: The value of the upper bound of the 95\
LOB: The value of the LOB (one column with identical values)
LOD: The value of the LOD (one column with identical values)
SLOPE: Value of the slope of the linear curve fit where only the spikes above LOD are considered
INTERCEPT: Value of the intercept of the linear curve fit where only the spikes above LOD are considered
NAME: The name of the assay (identical to that provided in the input)
METHOD which is always set to NONLINEAR when this function is used.
Each line of the data frame corresponds to a unique concentration value at which the value of the fit and prediction interval are evaluated.
More unique concentrations values than in the input data frame are used to increase the accuracy of the LOB/D calculations.
1 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.