getRTNormalizedMatrix {NormalyzerDE} | R Documentation |
The function orders the retention times and steps through them using the supplied step size (in minutes). If smaller than a fixed lower boundary the window is expanded to ensure a minimum amount of data in each normalization step. An offset can be specified which can be used to perform multiple RT-segmentations with partial overlapping windows.
getRTNormalizedMatrix(rawMatrix, retentionTimes, normMethod, stepSizeMinutes = 1, windowMinCount = 100, offset = 0)
rawMatrix |
Target matrix to be normalized |
retentionTimes |
Vector of retention times corresponding to rawMatrix |
normMethod |
The normalization method to apply to the time windows |
stepSizeMinutes |
Size of windows to be normalized |
windowMinCount |
Minimum number of values for window to not be expanded. |
offset |
Whether time window should shifted half step size |
Normalized matrix
data(example_data_small) data(example_design_small) data(example_data_only_values) dataMat <- example_data_only_values retentionTimes <- as.numeric(example_data[, "Average.RT"]) performCyclicLoessNormalization <- function(rawMatrix) { log2Matrix <- log2(rawMatrix) normMatrix <- limma::normalizeCyclicLoess(log2Matrix, method="fast") colnames(normMatrix) <- colnames(rawMatrix) normMatrix } rtNormMat <- getRTNormalizedMatrix(dataMat, retentionTimes, performCyclicLoessNormalization, stepSizeMinutes=1, windowMinCount=100)