plot_expression_profiles {GWENA} | R Documentation

## Modules expression profiles

### Description

Plot expression profiles for all modules with eigengene highlighted

### Usage

    plot_expression_profiles(
      data_expr,
      modules,
      eigengenes = NULL,
      alpha_expr = 0.3,
      ...
    )

### Arguments

`data_expr` | matrix or data.frame or SummarizedExperiment, expression data with genes as column and samples as row.
`modules` | vector, id (whole number or string) of modules associated to each gene.
`eigengenes` | matrix or data.frame, eigeingenes of the provided modules. If null, new ones will be computed with a PCA.
`alpha_expr` | numeric, transparency of the expression lines. Must be a value betweem 0 (transparent) and 1 (opaque)
`...` | additional parameters to pass to ggplot2::theme

### Details

The sign of the eigengenes from `detect_modules` may differ from the ones computed by the pca if no eigengenes is provided to `plot_expression_profiles` and therefore the plot itself. This is du to the sign indeterminancy property from the singular value decomposition.

### Value

A ggplot representing expression profile and eigengene by module

### Examples

    df <- kuehne_expr[1:24, 1:350]
    net <- build_net(df, n_threads = 1)
    detection <- detect_modules(df, net$network, detailled_result = TRUE)
    plot_expression_profiles(df, detection$modules, detection$modules_eigengenes)

[Package GWENA version 1.2.0 Index]