normR: Normalization by R score method

In eg-r/sights: Statistics and dIagnostic Graphs for HTS

Normalization by R score method

Description

Apply Robust Regression model separately to each plate

Usage

normR(dataMatrix, plateRows, plateCols, dataRows = NULL, dataCols = NULL)

Arguments

dataMatrix	Data frame or numeric matrix. Columns are plates, and rows are plate wells.
plateRows, plateCols	Number of rows/columns in plate.
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

R score normalization uses the robust regression method described by Wu et al (2008). Parameters are estimated through the rlm function. Data is pre-normalized by median normalization prior to applying the regression algorithm. R scores are the residuals produced by the model and rescaled by dividing with the standard deviation estimate from the regression function.

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

Wu et al. (2008). Quantitative Assessment of Hit Detection and Confirmation in Single and Duplicate High-Throughput Screenings. Journal of Biomolecular Screening, 13(2), 159-167.

See Also

Other normalization methods: normLoess, normMedFil, normRobZ, normSPAWN, normZ

Examples

## load dataset
data(ex_dataMatrix)

## apply R score
ex_normMatrix <- normR(dataMatrix = ex_dataMatrix, dataCols = 5:10,
plateRows = 8, plateCols = 10)

eg-r/sights documentation built on Jan. 28, 2023, 12:17 a.m.