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

Description

This function takes the output of gene_set_enrichment() and creates a heatmap visualization of the results.

Usage

gene_set_enrichment_plot(
  enrichment,
  xlabs = unique(enrichment$ID),
  PThresh = 12,
  ORcut = 3,
  enrichOnly = FALSE,
  layerHeights = c(0, seq_len(length(unique(enrichment$test)))) * 15,
  mypal = c("white", (grDevices::colorRampPalette(RColorBrewer::brewer.pal(9,
    "YlOrRd")))(50)),
  cex = 1.2
)

Arguments

`enrichment`	The output of `gene_set_enrichment()`.
`xlabs`	A vector of names in the same order and length as `unique(enrichment$ID)`. Gets passed to `layer_matrix_plot()`.
`PThresh`	A `numeric(1)` specifying the P-value threshold for the maximum value in the `-log10(p)` scale.
`ORcut`	A `numeric(1)` specifying the P-value threshold for the minimum value in the `-log10(p)` scale for printing the odds ratio values in the cells of the resulting plot.
`enrichOnly`	A `logical(1)` indicating whether to show only odds ratio values greater than 1.
`layerHeights`	A `numeric()` vector of length equal to `length(unique(enrichment$test)) + 1` that starts at 0 specifying where to plot the y-axis breaks which can be used for re-creating the length of each brain layer. Gets passed to `layer_matrix_plot()`.
`mypal`	A vector with the color palette to use. Gets passed to `layer_matrix_plot()`.
`cex`	Passed to `layer_matrix_plot()`.

Details

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 plot visualizing the gene set enrichment odds ratio and p-value results.

Author(s)

Andrew E Jaffe, Leonardo Collado-Torres

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_sfari_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_sfari_geneList,
    modeling_results = modeling_results,
    model_type = "enrichment"
)

## Visualize the gene set enrichment results
## with a custom color palette
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    mypal = c(
        "white",
        grDevices::colorRampPalette(
            RColorBrewer::brewer.pal(9, "BuGn")
        )(50)
    )
)

## Specify the layer heights so it resembles more the length of each
## layer in the brain
gene_set_enrichment_plot(
    asd_sfari_enrichment,
    xlabs = gsub(".*_", "", unique(asd_sfari_enrichment$ID)),
    layerHeights = c(0, 40, 55, 75, 85, 110, 120, 135),
)

LieberInstitute/spatialLIBD documentation built on Nov. 4, 2024, 11:57 a.m.