A curated R package of reusable helper functions and thin wrappers for immunology and cancer-genomics analysis — colour handling, differential-expression volcano plots, heatmaps, dendrograms, gene-ID conversion, gene-set enrichment, TCGA survival analysis, and single-cell (Seurat) helpers.
Installs light. Heavy Bioconductor dependencies (Seurat, TCGAbiolinks, biomaRt, clusterProfiler, org.*.eg.db, …) are optional — each function checks for the packages it needs at call time, so the base install is quick.
# install.packages("devtools")
devtools::install_github("Eomesodermin/r-utility-functions")
library(usefulfunctions)| Area | Functions |
|---|---|
| Colours | make_transparent(), get_batlow() |
| Transforms | moving_average(), standardize() |
| Heatmaps / dendrograms | basic_heatmap(), dendrogram_samples() |
| Volcano plots | custom_enhanced_volcano(), clean_volcano_data(), colour_volcano_points(), alpha_volcano_points(), size_volcano_points() |
| Gene IDs | convert_mouse_to_human(), convert_human_to_mouse() |
| Enrichment | go_enrichment() |
| TCGA | tcga_survival(), download_tcga_rnaseq() |
| Single-cell | umap_optimise(), sc_correlation(), correlation_heatmaps(), plot_correlation() |
Every function is documented (?function_name). The previous dot.case names
(makeTransparent, GO.function, TCGA.OS, …) remain as deprecated aliases,
so existing scripts keep working.
# Robustly standardise an expression matrix, then plot a heatmap
z <- standardize(expr_matrix)
basic_heatmap(z, Col.cluster = TRUE, Row.cluster = TRUE)
# Gene-gene correlation across single cells
cor_df <- sc_correlation(seurat_data_matrix, goi = "NKG7")Author: Dillon Corvino · dilloncorvino.com