This project demonstrates a minimal immune repertoire analysis pipeline using Change-O formatted B-cell receptor (BCR) data. It performs clone size analysis and calculates key diversity metrics like Shannon and Simpson’s reciprocal index, with visualizations per sample. Designed as a lightweight, reproducible example to support immune repertoire data analysis in R.
- Clone size distribution analysis
- Shannon diversity index (overall & per sample)
- Simpson’s reciprocal diversity index (per sample)
- Modular R script
- Output plots and data tables
- Easy to extend or Dockerize
The pipeline uses a single Change-O formatted file (example_db.tsv) containing annotated BCR sequences. This file is sourced from the alakazam R package example dataset.
| Column | Description |
|---|---|
SAMPLE |
Sample ID |
CLONE |
Clone assignment ID |
SEQUENCE_IMGT |
Full BCR sequence |
DUPCOUNT |
Number of reads for this sequence |
| ... | Other immune receptor annotations |
git clone https://github.com/PSBioinfo/AIRR-Pipeline.git
cd AIRR-Pipelineinstall.packages(c("dplyr", "ggplot2", "alakazam"))Rscript scripts/clone_analysis.R| File | Description |
|---|---|
output/clone_histogram.png |
Histogram of clone sizes |
output/shannon_index.txt |
Overall Shannon index |
output/shannon_by_sample.tsv |
Per-sample Shannon indices |
output/shannon_by_sample.png |
Bar plot of Shannon indices |
output/simpson_by_sample.tsv |
Per-sample Simpson indices |
output/simpson_by_sample.png |
Bar plot of Simpson indices |
AIRR-Pipeline/ ├── data/ │ └── example_db.tsv # Input BCR data ├── scripts/ │ └── clone_analysis.R # Main analysis script ├── output/ # All result files and plots ├── README.md # This file!
This project uses immune repertoire sequencing (AIRR-seq) data to analyze clonal diversity -- a key feature in immunological studies, cancer, and vaccine response. It mimics basic functionality from the Immcantation framework using base R packages.
This project is open source and freely available under the MIT License.