normRobZ {sights} | R Documentation

## Normalization by robust Z score method

### Description

Apply robust Z score to data

### Usage

    normRobZ(dataMatrix, dataRows = NULL, dataCols = NULL)

### Arguments

`dataMatrix` | Data frame or numeric matrix. Columns are plates, and rows are plate wells.
`dataRows, dataCols` | Optional integer vector. Indicate which row/column numbers from the dataMatrix should be normalized. If NULL then all rows/columns from the dataMatrix are used.

### Details

Robust Z score normalization subtracts the median of the raw well intensities of a given plate from the signal intensity of a given compound and divides it by the median absolute deviation of the raw well intensities of that plate.

### Value

Numeric matrix of normalized data in the same format as dataMatrix

### Note

For information on how to arrange your dataset for dataMatrix, please see (`ex_dataMatrix`)

### References

Malo et al. (2006). Statistical practice in high-throughput screening data analysis. Nature Biotechnology, 24(2), 167-175.

### See Also

Other normalization methods: `normLoess`, `normMedFil`, `normR`, `normSPAWN`, `normZ`

### Examples

    ## load dataset
    data(ex_dataMatrix)

    ## apply robust Z score
    ex_normMatrix <- normRobZ(dataMatrix = ex_dataMatrix, dataCols = 5:10)

[Package sights version 1.20.0 Index]