immuneREF is an R package that enables the analysis of repertoire similarity on a one-to-one, one-to-many and many-to-many scale across repertoire features ranging from fully sequence- to fully frequency-dependent features. This results in a thorough characterization of repertoire datasets for applications ranging from quality control to the search for disease-associated repertoire characteristics.
Documentation: https://immuneREF.readthedocs.io
Publication: https://www.biorxiv.org/content/10.1101/2022.01.23.476436v1
To be able to install immuneREF, the following prerequisites need to be fulfilled:
- R >= 3.4.0.
- Imports: kebabs, igraph, Biostrings, stringdist, vegan, doMC, foreach, dplyr, ggplot2, ggiraphExtra, grid, ComplexHeatmap
# Check R version
version[['version.string']]
# Install required R packages hosted on CRAN
install.packages(c("ggplot2","igraph","stringdist","vegan","doParallel","foreach","dplyr","grid"))
# Install required R packages hosted on Bioconductor
#If R version ≥ "4.0""
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("Biostrings","kebabs","ComplexHeatmap"))
#If R version < "4.0"
source("https://bioconductor.org/biocLite.R")
biocLite(c("Biostrings","kebabs","ComplexHeatmap"))
The package can be installed via GitHub.
Installation via GitHub:
- Check if all the prerequisites are fulfilled/installed.
- Execute the following lines in R:
# Install the devtools package
install.packages("devtools")
# Load devtools and install immuneREF from github
library(devtools)
install_github("GreiffLab/immuneREF")
# Test if installation was successful
library(immuneREF)
The quickstart workflow in immuneREF_quickstart.R shows the simplest application of 'immuneREF'. In it we run an analysis on a tutorial repertoire dataset consisting of four simulated immune repertoires (included in the package). At the end of the quickstart script, a heatmap visualizing the similarity landscape of the tutorial repertoires is generated. For a more detailed, step-by-step analysis we additionally provide a tutorial R script (immuneREF_tutorial.R)
immueREF_quickstart.R, provides a simple example of an immuneREF analysis that includes 3 steps: (i) Extraction of repertoire features, (ii) Calculation of feature-specific similarity between repertoire pairs and (iii) visualization of the results.
library(immuneREF)
# Calculate simularity networks for single features
similarity_networks <- immuneREF_quickstart(repertoire_list = tutorial_repertoires)
# Calculate network features and plot heatmap of repertoire similarities
network_features <- analyze_similarity_network(similarity_networks[["Condensed"]])
pheatmap::pheatmap(similarity_networks[["Condensed"]],scale='row')