DaMiR.iTSadjust: Batch correction of normalized Independent Test Set

In BioinfoMonzino/DaMiRseq: Data Mining for RNA-seq data: normalization, feature selection and classification

Description

This function aims to perform a batch correction on a normalized independent test set, exploiting the ComBat function of the sva package.

Usage

DaMiR.iTSadjust(adj_Learning_set, norm_Ind_Test_set, iTS_batch)

Arguments

adj_Learning_set	A SummarizedExperiment object or a data frame/matrix of adjusted and normalized data, obtained by the DaMiR.SVadjust function.
norm_Ind_Test_set	A data frame or a matrix of normalized data. The independent test set is supposed to be already normlaized by the DaMiR.iTSnorm function
iTS_batch	(Optional). A factor or a data.frame, containing information regarding experimental batches of the independent test set. Users can ignore this argument, if the independent test set is deemed a single experimental batch.

Details

The function applied a batch correction procedure to the independent test set, normalized by DaMiR.iTSnorm.

Value

A matrix containing a normalized and adjusted expression matrix (log2 scale).

Author(s)

Mattia Chiesa, Luca Piacentini

References

Jeffrey T. Leek, W. Evan Johnson, Hilary S. Parker, Elana J. Fertig, Andrew E. Jaffe and John D. Storey (2016). sva: Surrogate Variable Analysis. R package version 3.22.0.

See Also

ComBat

Examples

# use example data:
data(SE)

BioinfoMonzino/DaMiRseq documentation built on Aug. 22, 2021, 3:11 p.m.