Skip to content

Quick Start

A five‑minute tour: load immunarch, get example data, run core analyses, and ingest AIRR data with the bundled immundata tools.

1) Load the toolkit

library(immunarch)

2) Get example data and set a grouping

# Small demo dataset
idata <- get_test_idata() |> agg_repertoires("Therapy")

# Print a compact summary
idata

3) First‑look analyses

# Gene usage (e.g., V gene)
airr_stats_genes(idata, gene_col = "v_call") |> vis()

# Publicity / overlap
airr_public_jaccard(idata) |> vis()

# Clonality (proportion bins)
airr_clonality_prop(idata)

# Diversity (evenness)
airr_diversity_pielou(idata) |> vis()

4) (Optional) Annotate clonality per receptor and plot in Seurat

# Add per‑receptor clonality labels
idata <- annotate_clonality_prop(idata)

# Copy labels to a Seurat object by barcode and color UMAP
# (Assumes you created `sdata` earlier in your workflow)
sdata <- annotate_seurat(idata, sdata, cols = "clonal_prop_bin")
Seurat::DimPlot(sdata, reduction = "umap", group.by = "clonal_prop_bin", shuffle = TRUE)

5) (Optional) Ingest AIRR data with the bundled data layer

immundata ships with immunarch. You can call its readers directly for flexible ingestion.

# Read AIRR TSVs (toy example)
md_path <- system.file("extdata/tsv", "metadata.tsv", package = "immundata")
files <- c(
    system.file("extdata/tsv", "sample_0_1k.tsv", package = "immundata"),
    system.file("extdata/tsv", "sample_1k_2k.tsv", package = "immundata")
)

md <- read_metadata(md_path)
idata <- read_repertoires(
path     = files,
schema   = c("cdr3_aa", "v_call"),
metadata = md
)

# Continue with immunarch analyses
idata |> agg_repertoires("Therapy") |> airr_clonality_prop()

Next steps