plot_signal_condition_exp {spqn} | R Documentation

## Plot the signal and background distribution of a correlation matrix.

### Description

This function allows users to visualize the distributions of (assumed) signal and background, conditional on expression levels. The predicted signals are defined by the 0.1% highest correlations in each bin.

### Usage

    plot_signal_condition_exp(cor_mat, ave_exp, signal)

### 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
`signal` | a value between 0 and 1 giving the fraction of correlations which should be considered signal. We often use a value of `0.001`.

### 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
      plot_signal_condition_exp(cor_mat, ave_exp=ave_logrpkm, signal=0.05)}

[Package spqn version 1.2.0 Index]