immunarch
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.
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news and updates.
In order to install immunarch
execute the following
command:
install.packages("immunarch")
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.
immunarch
data1) Load the package and the data
library(immunarch) # Load the package into R
data(immdata) # Load the test dataset
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[[1]]) %>% 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
library(immunarch) # Load the package into R
immdata <- repLoad("path/to/your/data") # Replace it with the path to your data. Immunarch automatically detects the file format.
For advanced methods such as clonotype annotation, clonotype tracking, k-mer analysis and public repertoire analysis see “Tutorials”.
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 httr
and usethis
. In order to
reinstall a package you need to execute the command
install.packages("package_name")
, where
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: xcode-select –install
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
immunarch
:
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 rgl
package:
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
Remove the 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:
Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS="true")
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
devtools::install_local
function:
In normalizePath(path.expand(path), winslash, mustWork) :
path[1]="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 [email protected] (in case of private data).