normalize_correlation: Spatial quantile normalization (SpQN)
In spqn: Spatial quantile normalization

Description Usage Arguments Value Examples

View source: R/spqn.R

This method was developed to remove a mean-correlation relationship in correlation matrices built from gene expression data. It can serve as pre-processing step prior to a co-expression analysis.

1	normalize_correlation(cor_mat, ave_exp, ngrp, size_grp, ref_grp)

`cor_mat`	A (square and symmetrix) correlation matrix.
`ave_exp`	A vector of expression levels, same length as the number of rows of the correlation matrix in `cor_mat`. For other types of data, `ave_exp` can be the vector corresponding to the row/column of the correlation matrix, whose dependency with the distribution of correlations need to be removed.
`ngrp`	Number of bins in each row/column to be used to partition the correlation matrix, integer.
`size_grp`	Size of the outer bins to be used to appriximate the distribution of the inner bins, in order to smooth the normalization. Note that the product of size_grp and ngrp must be equal or larger than than the row/column number of cor_mat, and there is no smoothness in the normalization when they are equal.
`ref_grp`	Location of the reference bin on the diagonal, whose distribution will be used as target distribution in the normalization, an integer.

A normalized correlation matrix.

if(require(spqnData)){
  data(gtex.4k)
  cor_ori <- cor(t(assay(gtex.4k)))
  ave_logrpkm <- rowData(gtex.4k)$ave_logrpkm
  normalize_correlation(cor_ori, ave_exp = ave_logrpkm,
                        ngrp=10, size_grp=15, ref_grp=9)}