Use Conda Environment
Conda is an open source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs and updates packages and their dependencies.
SystempipeR is also available through conda environment.
Install conda
conda can be installed on different OS. Please find your system information, and the according method to install on conda installation page.
Create a conda environemnt
Conda environment is an isolated space where users can install tools and packages specifically to each project with different versions. To create a conda environment, on your bash console, use:
# create an environment called "myenv" and install the
# latest release version of R
conda create -n myenv r-essentials r-base
Here is the simplest way to create the environment. There are more options in environment creation. Please read the Managing environments section for more options.
To work in the new environment, use:
conda activate myenv
Other versions of R
To install other versions of R, one would need to take two steps:
First, only create the environment and activate it.
conda create -n myenv
conda activate myenv
Then, install the version of R you want
# this installs R 4.3
conda install -c conda-forge r-base=4.3.0 r-essentials
Install packages
One could use the traditional R way of installing packages after environment activation.
conda activate myenv
R
# for CRAN
install.packages(c("dplyr"))
# for Bioconductor
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("systemPipeR")
Since some packages have system dependencies, and we are working with a conda
environment, one could use conda install instead. This would also install most
system dependencies for you also. For example:
# systemPipeR
conda install -c bioconda bioconductor-systempiper
# systemPipeShiny
conda install -c bioconda bioconductor-systempipeshiny
The version of packages on bioconda is usually weeks or a months behind the versions on Bioconductor, especially when there is a new Bioconductor new release. Please use
BiocManagerordevtoolsto install the lastest package.
Exit environment
To exit or swtch different environments, use this first:
conda deactivate
Install command-line tools
Running bioinformatic analysis in systemPipeR often requires command-line tools,
such as samtools, hisat2, gatk,
to be installed and the tools need to be callable from current R environment.
Installing these tools usually requires one to also install the system dependencies, and compiling may also be needed. However, most times, conda is able to figure out the right system dependencies and can download the binary complied files directly for you. Therefore, installing these tools with conda is much easier.
Here we demonstate how to install samtools as an example.
- Go to anaconda and search the tool you want to install.
- If you type the name correctly, the tool should be the first result of the search.
- Click the results, you should see the install instruction page.
- Copy the code and we can start to install.
After we activate conda, we can directly type samtools on console to check.
However, sometimes if a tool is callable from console does not mean it can be
found in R environment. It is usually related to PATH problems, but can be complicated. Here is not expanded. A better way of checking in R is to use
tryCMD function in systemPipeR. Please see Before running section for details.
lz@hpcc:~/test$ conda activate myenv
(myenv)lz@hpcc:~/test$ samtools
# -bash: samtools: command not found
(myenv)lz@hpcc:~/test$ Rscript -e "systemPipeR::tryCMD('samtools')"
#ERROR:
# samtools : COMMAND NOT FOUND.
#Please make sure to configure your PATH environment variable according to the software in use.
After the two ways of checking, we can see samtools is not installed. To install,
copy the code from anaconda and run
(myenv)lz@hpcc:~/test$ conda install -c bioconda samtools
#Collecting package metadata (current_repodata.json): done
#Solving environment: done
#
### Package Plan ##
# environment location: /rhome/lz/shared/le/py/myenv
#
# added / updated specs:
# - samtools
#
#The following packages will be downloaded:
#
# package | build
# ---------------------------|-----------------
# c-ares-1.19.0 | h5eee18b_0 118 KB
# ------------------------------------------------------------
# Total: 118 KB
#
#The following NEW packages will be INSTALLED:
#
# _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main
# _openmp_mutex pkgs/main/linux-64::_openmp_mutex-5.1-1_gnu
# bzip2 pkgs/main/linux-64::bzip2-1.0.8-h7b6447c_0
# c-ares pkgs/main/linux-64::c-ares-1.19.0-h5eee18b_0
# ca-certificates pkgs/main/linux-64::ca-certificates-2023.01.10-h06a4308_0
# curl pkgs/main/linux-64::curl-7.88.1-h5eee18b_0
# krb5 pkgs/main/linux-64::krb5-1.19.4-h568e23c_0
# libcurl pkgs/main/linux-64::libcurl-7.88.1-h91b91d3_0
# libedit pkgs/main/linux-64::libedit-3.1.20221030-h5eee18b_0
# libev pkgs/main/linux-64::libev-4.33-h7f8727e_1
# libgcc-ng pkgs/main/linux-64::libgcc-ng-11.2.0-h1234567_1
# libgomp pkgs/main/linux-64::libgomp-11.2.0-h1234567_1
# libnghttp2 pkgs/main/linux-64::libnghttp2-1.46.0-hce63b2e_0
# libssh2 pkgs/main/linux-64::libssh2-1.10.0-h8f2d780_0
# libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-11.2.0-h1234567_1
# ncurses pkgs/main/linux-64::ncurses-6.4-h6a678d5_0
# openssl pkgs/main/linux-64::openssl-1.1.1t-h7f8727e_0
# samtools bioconda/linux-64::samtools-1.6-hb116620_7
# xz pkgs/main/linux-64::xz-5.2.10-h5eee18b_1
# zlib pkgs/main/linux-64::zlib-1.2.13-h5eee18b_0
#
#Proceed ([y]/n)? y
#
#Downloading and Extracting Packages
#
#Preparing transaction: done
#Verifying transaction: done
#Executing transaction: done
#(myenv)lz@hpcc:~/test$ which samtools
When conda finishes installation, we can check again
(myenv)lz@hpcc:~/test$ which samtools
#~/test/myenv/bin/samtools
(myenv)lz@hpcc:~/test$ Rscript -e "systemPipeR::tryCMD('samtools')"
#[1] "All set up, proceed!"
Both which command and tryCMD function return positive results.
Specify version
Similar to installation of R, you can specify the version number for command-line
tools as well. Different workflows may require different software versions. In
systemPipeR, after loading the workflow, you can use listCmdTools and listCmdModules to check required tools for current workflow. The version number
is usually listed in listCmdModules. See Before running.
listCmdModulesis usually used for modular system, but it is okay if you do not have it. It is helpful to display the version number.
Above, for example, the latest possible version is installed by default.
If we want to install satmools version 1.5.
conda install -y -c bioconda samtools=1.5
Work with Rstudio
Unfortunately, the free version of Rstudio does not provide support for running R from conda as of today (May, 2023). We would recommend using JupyterLab as your IDE. The installation of JupyterLab from conda can be found here.