myTAI (version 2.3.4)

plot_gene_profiles: Plot Individual Gene Expression Profiles

Description

Create a plot showing expression profiles for individual genes across developmental stages or cell types, with various visualization options.

Usage

plot_gene_profiles(
  phyex_set,
  genes = NULL,
  show_set_mean = FALSE,
  show_reps = FALSE,
  transformation = c("log", "std_log", "none"),
  colour_by = c("manual", "strata", "stage"),
  colours = NULL,
  max_genes = 100,
  show_labels = TRUE,
  label_size = 1.75,
  show_legend = TRUE,
  facet_by_strata = FALSE
)

Value

A ggplot2 object showing gene expression profiles

Arguments

phyex_set

A PhyloExpressionSet object (BulkPhyloExpressionSet or ScPhyloExpressionSet)

genes

Character vector of gene IDs to plot. If NULL, top expressing genes are selected

show_set_mean

Logical indicating whether to show the mean expression across all genes (default: FALSE)

show_reps

Logical indicating whether to show individual replicates (bulk) or cells (single-cell) (default: FALSE)

transformation

Character string specifying expression transformation: "log" (log1p), "std_log" (standardized log1p), or "none" (default: "log")

colour_by

Character string specifying coloring scheme: "strata" (by phylostratum), "stage" (by developmental stage/cell type), or "manual" (default: "manual")

colours

Optional vector of colors for manual coloring (default: NULL)

max_genes

Maximum number of genes to plot when genes=NULL (default: 100)

show_labels

Logical indicating whether to show gene labels (default: TRUE)

label_size

Font size of gene id labels if shown (default: 0.5).

show_legend

Logical indicating whether to show legend (default: TRUE)

facet_by_strata

Logical indicating whether to facet by phylostratum (default: FALSE)

Author

Filipa Martins Costa, Stefan Manolache, Hajk-Georg Drost

Details

This function creates detailed visualizations of individual gene expression patterns across development (bulk data) or cell types (single-cell data). Genes can be colored by phylostratum or developmental stage, and various transformations can be applied to highlight different aspects of the data.

Examples

# Plot specific genes for bulk data
p1 <- plot_gene_profiles(example_phyex_set, genes = example_phyex_set@gene_ids[1:5])

# Plot for single-cell data with faceting by strata
p2 <- plot_gene_profiles(example_phyex_set_sc, facet_by_strata = TRUE)