Bioconductor package to visualize spatially-resolved transcriptomics data

View source: R/gene_set_enrichment_plot.R

gene_set_enrichment_plot

R Documentation

Plot the gene set enrichment results with ComplexHeatmap

Description

This function takes the output of gene_set_enrichment() and creates a ComplexHeatmap visualization of the results. Fill of the heatmap represents the -log10(p-val), Odds-ratios are printed for test that pass specified significance threshold ORcut.

Usage

gene_set_enrichment_plot(
  enrichment,
  xlabs = unique(enrichment$ID),
  PThresh = 12,
  ORcut = 3,
  enrichOnly = FALSE,
  mypal = c("white", RColorBrewer::brewer.pal(9, "YlOrRd")),
  plot_SetSize_bar = FALSE,
  gene_list_length = NULL,
  model_sig_length = NULL,
  model_colors = NULL,
  ...
)

Arguments

`enrichment`	The output of `gene_set_enrichment()`.
`xlabs`	A vector of names in the same order and length as `unique(enrichment$ID)`.
`PThresh`	A `numeric(1)` specifying the P-value threshold for the maximum value in the `-log10(p)` scale.
`ORcut`	A `numeric(1)` specifying the P-value threshold for the minimum value in the `-log10(p)` scale for printing the odds ratio values in the cells of the resulting plot. Defaults to 3 or p-val < 0.001.
`enrichOnly`	A `logical(1)` indicating whether to show only odds ratio values greater than 1.
`mypal`	A `character` vector with the color palette to use. Colors will be in order from 0 to lowest P-val `max(-log(enrichment$Pval))`. Defaults to white, yellow, red pallet.
`plot_SetSize_bar`	A `logical(1)` indicating whether to plot SetSize from `enrichment` as an `anno_barplot` at the top of the heatmap.
`gene_list_length`	Optional named `numeric` vector indicating the length of the `gene_list` used to calculate `enrichment`, if included and `plot_setSize_bar = TRUE` then the top `anno_barplot` will show the `SetSize` and the difference from the length of the input gene_list.
`model_sig_length`	Optional named `numeric` vector indicating the number of significant genes in `modeling_results` used to calculate `enrichment`. If included `anno_barplot` will be added to rows.
`model_colors`	named `character` vector of colors. It adds colors to row annotations.
`...`	Additional parameters passed to `ComplexHeatmap::Heatmap()`.

Details

Includes functionality to plot the size of the input gene sets as barplot annotations.

Check https://github.com/LieberInstitute/HumanPilot/blob/master/Analysis/Layer_Guesses/check_clinical_gene_sets.R to see a full script from where this family of functions is derived from.

Value

A (Heatmap-class) visualizing the gene set enrichment odds ratio and p-value results.

Author(s)

Andrew E Jaffe, Leonardo Collado-Torres, Louise Huuki-Myers

Examples


## Read in the SFARI gene sets included in the package
asd_sfari <- utils::read.csv(
    system.file(
        "extdata",
        "SFARI-Gene_genes_01-03-2020release_02-04-2020export.csv",
        package = "spatialLIBD"
    ),
    as.is = TRUE
)

## Format them appropriately
asd_safari_geneList <- list(
    Gene_SFARI_all = asd_sfari$ensembl.id,
    Gene_SFARI_high = asd_sfari$ensembl.id[asd_sfari$gene.score < 3],
    Gene_SFARI_syndromic = asd_sfari$ensembl.id[asd_sfari$syndromic == 1]
)

## Obtain the necessary data
if (!exists("modeling_results")) {
    modeling_results <- fetch_data(type = "modeling_results")
}

## Compute the gene set enrichment results
asd_sfari_enrichment <- gene_set_enrichment(
    gene_list = asd_safari_geneList,
    modeling_results = modeling_results,
    model_type = "enrichment"
)

## Visualize the gene set enrichment results

## Default plot
gene_set_enrichment_plot(
    enrichment = asd_sfari_enrichment
)

## Use a custom green color palette & use shorter gene set names
## (x-axis labels)
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    mypal = c("white", RColorBrewer::brewer.pal(9, "BuGn"))
)

## Add bar plot annotations for SetSize of model genes in the gene_lists
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    plot_SetSize_bar = TRUE
)

## Add stacked bar plot annotations showing SetSize and difference from the
## length of the input gene_list
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    plot_SetSize_bar = TRUE,
    gene_list_length = lapply(asd_safari_geneList, length)
)

## add bar plot annotations for number of enriched genes from layers
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")
sig_genes <- sig_genes_extract(
    modeling_results = modeling_results,
    model = "enrichment",
    sce_layer = sce_layer,
    n = nrow(sce_layer)
)

sig_genes <- sig_genes[sig_genes$fdr < 0.1, ]
n_sig_model <- as.list(table(sig_genes$test))

## add barplot with n significant genes from modeling
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    plot_SetSize_bar = TRUE,
    model_sig_length = n_sig_model
)

## add color annotations
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    plot_SetSize_bar = TRUE,
    model_colors = libd_layer_colors
)

## add barplot with n significant genes from modeling filled with model color
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    plot_SetSize_bar = TRUE,
    model_sig_length = n_sig_model,
    model_colors = libd_layer_colors
)

LieberInstitute/spatialLIBD documentation built on Dec. 19, 2024, 7:12 p.m.