cellHTS object.
This function calculates the repeatability standard deviation between replicate plates and the correlation coefficient between replicates. If there are more than 2 replicates, the minimum and maximum correlation between replicates is given. These measures are calculated only for sample wells.
getMeasureRepAgreement(x, corr.method = "spearman")cellHTS object. See details.cor.nrPlates x nrChannels;"corrCoef" (if the number of replicates equals 2): matrix with the correlation coefficients between plate replicates. It has dimensions: nrPlates x nrChannels;"corrCoef.min" (if the number of replicates is greater than 2): matrix with the minimum value of the correlation coefficients between plate replicates. It has dimensions nrPlates x nrChannels;"corrCoef.max" (if the number of replicates is greater than 2): matrix with the maximum value of the correlation coefficients between plate replicates. It has dimensions nrPlates x nrChannels.cellHTS object (state(x)[["configured"]]=TRUE), this function calculates the repeatability standard deviation between replicate plates and the correlation coefficient between plate replicates using only the sample wells. If there are more than 2 replicates, the minimum and maximum correlation value between pairs of replicates are given.These measures are calculated using the data values stored in slot assayData of the x.
For a given plate $p$, the repeatability standard deviation is determined as the square root of the average of the squared standard deviations ($sr$) calculated for each sample well $k$ by considering the measurement of all of the replicates:
$$RepStDev_{p} = \sqrt{\frac{\sum{sr^2}}{n_{k} } } $$
where $n_{k}$ is the total number of sample probes for plate $p$.
configure,
writeReport
data(KcViabSmall)
repAgree <- getMeasureRepAgreement(KcViabSmall)
x <- normalizePlates(KcViabSmall, scale="multiplicative", log=FALSE, method="median", varianceAdjust="none")
repAgree <- getMeasureRepAgreement(x)
Run the code above in your browser using DataLab