normRobZ: Normalization by robust Z score method

In sights: Statistics and dIagnostic Graphs for HTS

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)

sights documentation built on Nov. 8, 2020, 7:20 p.m.