In ebi-gene-expression-group/bioconductor-ExpressionAtlas: Search, download and visualise datasets from EMBL-EBI Expression Atlas and Single-Cell Expression Atlas

This vignette demonstrates how to access and analyze GTEX RNA-seq data from Expression Atlas. The example shows how to:

1. Search and retrieve GTEX data.
2. Get raw counts and normalized expression data (TPM and FPKM).
3. Create heatmaps for visualization of gene expression patterns.
4. Filter and analyze specific genes of interest across GTEX tissues.

The following example uses the ExpressionAtlas package to access E-GTEX-8 dataset (17350 samples).

knitr::opts_chunk$set(message=FALSE)
knitr::opts_chunk$set(warning=FALSE)

suppressMessages( library( ExpressionAtlas ) )

atlasRes <- searchAtlasExperiments( query = "gtex" )
atlasRes

gtex <- getAtlasExperiment( experimentAccession = "E-GTEX-8" )
gtex
gtex$rnaseq
assays( gtex$rnaseq )$counts[1:5,1:5]
dim( assays( gtex$rnaseq )$counts )
colData( gtex$rnaseq )
metadata( gtex$rnaseq )

gtex_tpm <- getNormalisedAtlasExpression( experimentAccession = "E-GTEX-8", normalisation = "tpm" )
head(gtex_tpm)

gtex_fpkm <- getNormalisedAtlasExpression( experimentAccession = "E-GTEX-8", normalisation = "fpkm" )
head(gtex_fpkm)

gtex_heatmap <- heatmapAtlasExperiment( df = gtex_tpm, filename = "E-GTEX-8-tpm-heatmap.pdf", save_pdf= FALSE, show_plot = TRUE, heatmap_color = "Reds", top_n = 50, show_heatmap_title = TRUE )


library(ComplexHeatmap)
library(dplyr)
library(RColorBrewer)

plot_gene_heatmap <- function(gtex_fpkm, selected_genes, color_scheme = "Reds") {

    gtex_filtered <- gtex_fpkm %>% filter(Gene.Name %in% selected_genes)

    if (nrow(gtex_filtered) == 0) {
        stop("None of the selected genes were found in the dataset.")
    }

    expr_matrix <- as.matrix(gtex_filtered[, -c(1, 2)])
    rownames(expr_matrix) <- gtex_filtered$Gene.Name

    # ensure matrix is numeric
    expr_matrix <- apply(expr_matrix, 2, as.numeric)

    col_fun <- colorRampPalette(brewer.pal(9, color_scheme))(100)

    Heatmap(
        t(scale(t( expr_matrix ))),
        name = "Expression",
        col = col_fun,
        cluster_rows = TRUE,
        cluster_columns = TRUE,
        show_row_names = TRUE,
        show_column_names = TRUE
    )
}

selected_genes <- c("CTCF", "TSPAN6", "TNMD", "DPM1", "SCYL3", "CBLIF", "CTCF", "DDX4", "STATH")
plot_gene_heatmap(gtex_fpkm, selected_genes, "RdBu")

ebi-gene-expression-group/bioconductor-ExpressionAtlas documentation built on July 4, 2025, 12:53 a.m.