plot_expression_profiles: Modules expression profiles

In Kumquatum/GWENA: Pipeline for augmented co-expression analysis

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)

Kumquatum/GWENA documentation built on July 7, 2023, 3:41 p.m.