qqplot_condition_exp {spqn} | R Documentation

## Q-Q plot for examing the distributions across submatrices of a correlation matrix.

### Description

We partition the correlation matrix into 10x10 bins of equal size, with genes ordered according to expression level. As reference bin, we choose the (9,9) bin (ie. the almost-highest expressed genes). We then make a QQ-plot of the (i,j)'th submatrix vs. the (9,9) submatrix. See the SpQN paper for detail on these choices.

### Usage

    qqplot_condition_exp(cor_mat,ave_exp, i,j)

### Arguments

`cor_mat` | Matrix, correlation matrix, generated by gene expression matrix.
`ave_exp` | Vector, average expression level of each gene for the normalized expression matrix.
`i` | Integer, row number of the submatrix (see details).
`j` | Integer, column number of the submatrix (see details).

### Value

Invoked for the side effect of producing a plot.

### Note

The mnemonic for `condition_exp` is ‘conditional on expression’.

### Examples

    if(require(spqnData)) {
      data(gtex.4k)
      cor_mat <- cor(t(assay(gtex.4k)))
      ave_logrpkm <- rowData(gtex.4k)$ave_logrpkm
      qqplot_condition_exp(cor_mat, ave_exp=ave_logrpkm, 1, 1)
    }

[Package spqn version 1.2.0 Index]