immunarch is an R package designed to analyse T-cell receptor (TCR) and B-cell receptor (BCR) repertoires, mainly tailored to medical scientists and bioinformaticians. The mission of
immunarch is to make immune sequencing data analysis as effortless as possible and help you focus on research instead of coding. Follow us on Twitter for news and updates.
In order to install
immunarch execute the following command:
That’s it, you can start using
immunarch now! See the Quick Start section below to dive into immune repertoire data analysis. If you run in any trouble during installation, take a look at the Installation Troubleshooting section.
Note: there are quite a lot of dependencies to install with the package because it installs all the widely-used packages for data analysis and visualisation. You got both the AIRR data analysis framework and the full Data Science package ecosystem with only one command, making
immunarch the entry-point for single-cell & immune repertoire Data Science.
If the above command doesn’t work for any reason, try installing
immunarch directly from its repository:
install.packages(c("devtools", "pkgload")) # skip this if you already installed these packages devtools::install_github("immunomind/immunarch") devtools::reload(pkgload::inst("immunarch"))
Since releasing on CRAN is limited to one release per one or two months, you can install the latest pre-release version with all the bleeding edge and optimised features directly from the code repository. In order to install the latest pre-release version, you need to execute the following commands:
install.packages(c("devtools", "pkgload")) # skip this if you already installed these packages devtools::install_github("immunomind/immunarch", ref="dev") devtools::reload(pkgload::inst("immunarch"))
You can find the list of releases of
immunarch here: https://github.com/immunomind/immunarch/releases
The gist of the typical TCR or BCR data analysis workflow can be reduced to the next few lines of code.
1) Load the package and the data
2) Calculate and visualise basic statistics
repExplore(immdata$data, "lens") %>% vis() # Visualise the length distribution of CDR3 repClonality(immdata$data, "homeo") %>% vis() # Visualise the relative abundance of clonotypes
3) Explore and compare T-cell and B-cell repertoires
repOverlap(immdata$data) %>% vis() # Build the heatmap of public clonotypes shared between repertoires geneUsage(immdata$data[]) %>% vis() # Visualise the V-gene distribution for the first repertoire repDiversity(immdata$data) %>% vis(.by = "Status", .meta = immdata$meta) # Visualise the Chao1 diversity of repertoires, grouped by the patient status
If you cannot install
devtools, check sections 1 and 2 below.
If you run into any other trouble, try the following steps:
Check your R version. Run
version command in the console to get your R versions. If the R version is below 3.5.0 (for example,
R version 3.1.0), try updating your R version to the most recent one. Note: if you try to install a package after the update and it still fails with the following message:
ERROR: dependencies ‘httr’, ‘usethis’ are not available for package ‘devtools’ * removing ‘/home/ga/R/x86_64-pc-linux-gnu-library/3.5/devtools’ Warning in install.packages : installation of package ‘devtools’ had non-zero exit status
it means that you need to reinstall the packages that were built under the previous R versions. In the example above those would be the packages
usethis. In order to reinstall a package you need to execute the command
package_name is the name of the package to update. To find the packages that need to be reinstalled after updating R, you need to look for installation messages like this in the installation process:
ERROR: package ‘usethis’ was installed by an R version with different internals; it needs to be reinstalled for use with this R version
Check if your packages are outdated and update them. In RStudio you can run the “Update” button on top of the package list in the “Package” window. In R console you can run the
old.packages() command to view a list of outdated packages. The following messages indicate that an update is required:
Error: package ‘dtplyr’ 0.0.3 was found, but >= 1.0.0 is required by ‘immunarch’ Execution halted ERROR: lazy loading failed for package ‘immunarch’
byte-compile and prepare package for lazy loading Error in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]) : namespace 'ggalluvial' 0.9.1 is being loaded, but >= 0.10.0 is required Calls: <Anonymous> ... namespaceImportFrom -> asNamespace -> loadNamespace Execution halted
For Mac users. Make sure to install XCode from App Store first and command line developers tools second by executing the following command in Terminal:
For Mac users. If you have other issues, for instance some old packages can’t be updated, or you see an error message such as
ld: warning: directory not found for option or
ld: library not found for -lgfortran, this link will help you to fix the issue.
For Mac Mojave (1.14) users. If you run into the following error:
/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/include/c++/v1/math.h:301:15: fatal error: 'math.h' file not found #include_next <math.h> ^~~~~~~~
Open Terminal, execute the following command and try again to install
sudo installer -pkg /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10.14.pkg -target /
For Linux users. If you have issues with the
igraph library or have Fortran errors such as:
** testing if installed package can be loaded from temporary location Error: package or namespace load failed for 'igraph' in dyn.load(file, DLLpath = DLLpath, ...): unable to load shared object '/usr/local/lib/R/site-library/00LOCK-igraph/00new/igraph/libs/igraph.so': libgfortran.so.4: cannot open shared object file: No such file or directory
See this link for help.
For Linux users. If you have issues with the
configure: error: missing required header GL/gl.h ERROR: configuration failed for package ‘rgl’
Install “mesa-common-dev” via OS terminal by executing the following command:
apt-get install mesa-common-dev
Check this link for more information and other possible workarounds.
If you have error messages with
rlang in them such as:
Error: .onLoad failed in loadNamespace() for 'vctrs', details: call: env_bind_impl(.env, list3(...), "env_bind()", bind = TRUE) error: object 'rlang_env_bind_list' not found
rlang package and install it again. This error is often happens after updating R to a newer version, while
rlang not being properly updated.
If you have error messages like the following (note the
(converted from warning) part):
** byte-compile and prepare package for lazy loading Error: (converted from warning) package 'ggplot2' was built under R version 3.6.1 Execution halted ERROR: lazy loading failed for package 'immunarch'
Execute the following command in R and try again to install the package:
For Windows users. If you encounter issues with the package installation, or if you want to change the folder for R packages, feel free to check this forum post.
For Windows users. Make sure to install Rtools. Before installation close RStudio, install Rtools and reopen it afterwards. To check if Rtools installed correctly, run the
devtools::find_rtools() command (after installing the devtools package). If you have an error, check this link for help.
If you cannot install dependencies for
immunarch, please consider manual installation of all dependencies by executing the following command in R console:
install.packages(c("rematch", "prettyunits", "forcats", "cellranger", "progress", "zip", "backports", "ellipsis", "zeallot", "SparseM", "MatrixModels", "sp", "haven", "curl", "readxl", "openxlsx", "minqa", "nloptr", "RcppEigen", "utf8", "vctrs", "carData", "pbkrtest", "quantreg", "maptools", "rio", "lme4", "labeling", "munsell", "cli", "fansi", "pillar", "viridis", "car", "ellipse", "flashClust", "leaps", "scatterplot3d", "modeltools", "DEoptimR", "digest", "gtable", "lazyeval", "rlang", "scales", "tibble", "viridisLite", "withr", "assertthat", "glue", "magrittr", "pkgconfig", "R6", "tidyselect", "BH", "plogr", "purrr", "ggsci", "cowplot", "ggsignif", "polynom", "fastcluster", "plyr", "abind", "dendextend", "FactoMineR", "mclust", "flexmix", "prabclus", "diptest", "robustbase", "kernlab", "GlobalOptions", "shape", "colorspace", "stringi", "hms", "clipr", "crayon", "httpuv", "mime", "jsonlite", "xtable", "htmltools", "sourcetools", "later", "promises", "gridBase", "RColorBrewer", "yaml", "ggplot2", "dplyr", "dtplyr", "data.table", "gridExtra", "ggpubr", "pheatma3", "ggrepel", "reshape2", "DBI", "factoextra", "fpc", "circlize", "tidyr", "Rtsne", "readr", "readxl", "shiny", "shinythemes", "treemap", "igraph", "airr", "ggseqlogo", "UpSetR", "stringr", "ggalluvial", "Rcpp"))
If you encounter the following error while running the
In normalizePath(path.expand(path), winslash, mustWork) : path="path/to/your/folder/with/immunarch.tar.gz": In file.copy(x$path, bundle, recursive = TRUE) : problem copying No such file or directory
Check your path to the downloaded package archive file. It should not be “path/to/your/folder/with/immunarch.tar.gz”, but a path on your PC to the downloaded file, e.g., “C:/Users/UserName/Downloads/immunarch.tar.gz” or “/Users/UserName/Downloads/immunarch.tar.gz”.
If any of the troubles still persist, let us know via GitHub (preferably) or firstname.lastname@example.org (in case of private data).