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:
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.
NAIR
support?NAIR
supports bulk and single-cell immune repertoire sequence data for
T-cell or B-cell receptors (TCR or BCR).
NAIR
model the immune repertoire as a network?To install the latest release version of NAIR
, use the following
command:
install.packages("NAIR")
To install the latest development version of NAIR
from source (which
requires compilation), use the following command:
devtools::install_github(
"mlizhangx/Network-Analysis-for-Repertoire-Sequencing-",
dependencies = TRUE,
build_vignettes = TRUE
)
General network analysis on AIRR-Seq data is performed using
buildRepSeqNetwork()
or its convenient alias buildNet()
. This
function does the following:
igraph
and adjacency matrix)See this vignette for a tutorial.
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.
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.
This
article
provides an introduction to the creation and customization of network
visualizations using NAIR
.
This
vignette
provides an introduction to computing node-level network properties with
NAIR
.
This
vignette
explains how to perform cluster analysis with NAIR
.
This
vignette
provides an overview of NAIR
utility functions that supplement the
main function buildNet()
.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.