getSmoothedRTNormalizedMatrix {NormalyzerDE} | R Documentation

## Generate multiple RT time-window normalized matrices where one is shifted. Merge them using a specified method (mean or median) and return the result.

### Description

Uses the function getRTNormalizedMatrix to generate multiple normalized matrices which are shifted respective to each other and finally merged into a single matrix. This could potentially reduce effect of fluctuations within individual windows.

### Usage

    getSmoothedRTNormalizedMatrix(rawMatrix, retentionTimes, normMethod,
      stepSizeMinutes, windowShifts = 2, windowMinCount = 100,
      mergeMethod = "mean", noLogTransform = FALSE)

### Arguments

`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
`windowShifts` | Number of frame shifts.
`windowMinCount` | Minimum number of features within window.
`mergeMethod` | Layer merging approach. Mean or median.
`noLogTransform` | Don't log transform the input

### Value

Normalized matrix

### Examples

    data(example_data_small)
    data(example_data_only_values)
    data(example_design_small)
    retentionTimes <- as.numeric(example_data[, "Average.RT"])
    dataMat <- example_data_only_values
    performCyclicLoessNormalization <- function(rawMatrix) {
        log2Matrix <- log2(rawMatrix)
        normMatrix <- limma::normalizeCyclicLoess(log2Matrix, method="fast")
        colnames(normMatrix) <- colnames(rawMatrix)
        normMatrix
    }
    rtNormMat <- getSmoothedRTNormalizedMatrix(dataMat, retentionTimes,
        performCyclicLoessNormalization, stepSizeMinutes=1, windowMinCount=100,
        windowShifts=2, mergeMethod="median")

[Package NormalyzerDE version 1.2.0 Index]