Introduction to the NAIR package

NAIR: Network Analysis of Immune Repertoire

NAIR is an R package for analyzing the adaptive immune repertoire using network analysis based on similarities among receptor sequences. It implements methods from the following paper:

Hai Yang, Jason Cham, Brian Neal, Zenghua Fan, Tao He and Li Zhang. (2023). NAIR: Network Analysis of Immune Repertoire. Frontiers in Immunology, vol. 14.

NAIR allows users to perform network analysis on Adaptive Immune Receptor Repertoire Sequencing (AIRR-Seq) data, including computing local and global network properties of nodes and clusters, which can provide insights into the structural organization of the immune repertoire network.

NAIR also enables users to search across multiple AIRR-Seq samples for clones/clusters associated with subject characteristics, disease conditions or clinical outcomes, as well as identify public clones/clusters. This can help researchers identify potentially important TCR/BCR clones.

To aid in interpretation of the immune repertoire network, NAIR includes convenient functionality for generating customized network visualizations.

What data does NAIR support?

NAIR supports bulk and single-cell immune repertoire sequence data for T-cell or B-cell receptors (TCR or BCR).

How does NAIR model and analyze the adaptive immune receptor repertoire as a network?

Getting Started

Main Function

General network analysis on AIRR-Seq data is performed using buildRepSeqNetwork() or its convenient alias buildNet(). This function does the following:

See vignette("buildRepSeqNetwork") for a tutorial.

Searching for Associated Clusters

Given multiple samples of bulk AIRR-Seq data, NAIR can be used to search for TCR/BCR clusters associated with a binary variable of interest, such as a disease condition, treatment or clinical outcome. See this article for a tutorial.

Searching for Public Clusters

The NAIR package includes a set of functions that facilitate searching for public TCR/BCR clusters across multiple samples of bulk AIRR-seq data. In this context, a public cluster consists of similar TCR/BCR clones (e.g., those whose CDR3 amino acid sequences differ by at most one amino acid) that are shared across samples (e.g., across individuals or across time points for a single individual). See this article for a tutorial.

Additional Resources


This article provides an introduction to the creation and customization of network visualizations using NAIR.

Network Properties and Cluster Analysis

vignette("node_properties") provides an introduction to computing node-level network properties with NAIR.

vignette("cluster_analysis") explains how to perform cluster analysis with NAIR.

Supplementary Functions

vignette("supplementary") provides an overview of NAIR utility functions that supplement the main function buildNet().