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UniverSC: Single-cell processing across technologies |
S. Thomas Kelly^1†^, Kai Battenberg^1,2†^, Makoto Hayashi^2^, Aki Minoda^1^ <br> ^1^ RIKEN Center for Integrative Medical Sciences, Suehiro-cho-1-7-22, Tsurumi Ward, Yokohama <br> ^2^ RIKEN Center for Sustainable Resource Sciences, Suehiro-cho-1-7-22, Tsurumi Ward, Yokohama <br> †These authors contributed equally to this work |
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Thursday 22 April 2021 |
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Table of Contents |
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Single-cell processing across technologies
Summary
Single-cell RNA-sequencing analysis to quantify RNA molecules in individual cells has become popular owing to the large amount of information one can obtain from each experiment. UniverSC is a universal single-cell processing tool that supports any UMI-based platform. Our command-line tool enables consistent and comprehensive integration, comparison, and evaluation across data generated from a wide range of platforms. Here we provide a guide to install and use this tool to process single-cell RNA-Seq data from FASTQ format.
Package
UniverSC version 1.0.3
Maintainers
Tom Kelly^†^ (RIKEN IMS) and Kai Battenberg^†^ (RIKEN CSRS/IMS)
†These authors contributed equally to this work
Contact: <first name>.<family name>[at]riken.jp
Disclaimer: we are third party developers not affiliated with 10X Genomics or any other vendor of single-cell technologies. We are releasing this code on an open-source license which calls Cell Ranger™ as an external dependency.
If you have cellranger already installed, then all you need to do is clone or download this git repository. You can then run the script in this directory or add it your PATH. See the Quick Start guide below.
If you wish to install cellranger and configure this script to run on a Linux environment, we provide details on installation below. Note that launch_universc.sh requires write-access a Cell Ranger installation so it needs to be installed in a user's "home" directory on a server. No admin powers needed!
Note that cellranger installations that are pre-compiled on Linux will not run on Mac or Windows. Note that Mac OS and some Linux distributions also have different version of sed and rename. It is possible to compile an open-source version of Cell Ranger but it is tricky to install the dependencies so we recommend using our docker image if you wish to do this.
If you are a beginner bioinformatician or wish to run this on a local computer (Mac or Windows), no problem! We provide a "docker" image containing everything needed to run it without installing the software needed. All you need to do is install docker and follow our guide to use the image. This comes bundled with all the compatible versions needed to run it.
Note that you need to run the shell commands given in a unix-like command-line interface (the "Terminal" application on Mac or Linux systems). Many shells are supported but we recommend the "bash" shell for beginners (this is the default on most systems). Windows 10 includes a subsystem to run bash. If this is too complicated, you can open a Linux environment (Ubuntu) in docker by following our instructions. Then you can enter bash commands into the terminal opened by docker.
If you run into problems installing or running launch_universc.sh please don't hesistate to contact us via email or GitHub.
We've developed a bash script that will run Cell Ranger on FASTQ files for these technologies. See below for details on how to use it.
If you use this tool, please cite to acknowledge the efforts of the authors. You can report problems and request new features to the maintainers with and issue on GitHub. Details on how to install and run are provided below. Please see the help and examples to try solve your problem before submitting an issue.
Details on the Docker image are given below. We recommend using Docker unless you have a server environment with Cell Ranger installed already.
In principle, any technology with a cell barcode and unique molecular identifier (UMI) can be supported.
The following technologies have been tested to ensure that they give the expected results: 10x Genomics, Nadia (DropSeq), ICELL8 version 3
We provide the following preset configurations for convenience based on published data and configurations used by other pipelines (e.g, DropSeqPipe and Kallisto/Bustools). To add further support for other technologies or troubleshoot problems, please submit an Issue to the GitHub repository: TomKellyGenetics/universc as described in Bug Reports below.
Some changes to the Cell Ranger install are required to run other technologies. Therefore we provide settings for 10x Genomics which restores settings for the Chromium instrument. We therefore recommend using 'convert' for processing all data from different technologies as the tool manages these changes. Please note that on a single install of Cell Ranger, multiple technologies or multiple samples of the same technology with different whitelist barcodes cannot be run cannot be run simultaneousely (the tool will also check for this to avoid causing problems with existing runs). Multiple samples of the same technology with the same barcode whitelist can be run simultaneously.
If you are using UniverSC you should also do so to run 10x Genomics data. If you wish to restore Cell Ranger to
default settings, see the installation or troubleshooting sections below.
- 10x Genomics (version automatically detected): 10x, chromium
- 10x Genomics version 2 (16bp barcode, 10bp UMI): 10x-v2, chromium-v2
- 10x Genomics version 3 (16bp barcode, 12bp UMI): 10x-v3, chromium-v3
- CEL-Seq (8bp barcode, 4bp UMI): celseq
- CEL-Seq2 (6bp UMI, 6bp barcode): celseq2
- Drop-Seq (12bp barcode, 8bp UMI): nadia, dropseq
- ICELL8 version 3 (11bp barcode, 14bp UMI): icell8 or custom
- inDrops
- inDrops version 1 (19bp barcode, 6bp UMI): indrops-v1, 1cellbio-v1
- inDrops version 2 (19bp barcode, 6bp UMI): indrops-v2, 1cellbio-v2
- MARS-Seq (6bp barcode, 10bp UMI): marsseq, marsseq-v1
- MARS-Seq2 (7bp barcode, 8bp UMI): marsseq2, marsseq-v2
- Quartz-Seq2 (14bp barcode, 8bp UMI): quartzseq2-384
- Quartz-Seq2 (15bp barcode, 8bp UMI): quartzseq2-1536
- SCRB-Seq (6bp barcode, 10bp UMI): scrbseq, mcscrbseq
- SeqWell (12bp barcode, 8bp UMI): seqwell
- Smart-seq, Smart-seq2 (16bp barcode, No UMI): smartseq2
- Smart-seq2-UMI, Smart-seq3 (16bp barcode, 8bp UMI): smartseq3
All technologies support 3' single-cell RNA-Seq. Barcode adjustments and
whitelists are changed automatically. For 5' single-cell RNA-Seq, this
is only supported for 10x Genomics version 2 chemistry. This is detected
automatically but can be configured with the --chemistry argument.
We are developing technologies to support dual indexes and full length scRNA kits.
Experimental technologies (not yet supported):
- inDrops version 3 (16bp barcode, 6bp UMI): indrops-v3, 1cellbio-v3
- Sci-Seq (8bp UMI, 30bp barcode): sciseq
- SPLiT-Seq (10bp UMI, 18bp barcode): splitseq
- SureCell (18bp barcode, 8bp UMI): surecell, ddseq, biorad
For dual-indexed technologies such as inDrops-v3, Sci-Seq, SmartSeq3 it is advised to use "bcl2fastq" before calling UniverSC:
/usr/local/bin/bcl2fastq -v --runfolder-dir "/path/to/illumina/bcls" --output-dir "./Data/Intensities/BaseCalls"\
--sample-sheet "/path/to/SampleSheet.csv" --create-fastq-for-index-reads\
--use-bases-mask Y26n,I8n,I8n,Y50n --mask-short-adapter-reads 0\
--minimum-trimmed-read-length 0
Custom inputs are also supported by giving the name "custom" and length of barcode and UMI separated by a "_" character.
e.g. Custom (16bp barcode, 10bp UMI): custom_16_10
Custom barcode files are also supported for preset technologies. These are particularly useful for well-based technologies to demutliplex based on the wells.
This tool will be released open-source (see legal stuff below). We welcome any feedback on it and any contributions to improve it. Hopefully it will save people time by making it easier to compare technologies.
We have tested it on several technologies but we need users like you to let us know how we can improve it. We hope that it will save you time by handing tedious parts of data formatting so that you can focus on the results.
A submission to a journal and biorXiv is in progress. Please cite these when they are available. Currently, the package can be cited as follows:
Kelly, S.T., Battenberg, Hetherington, N.A., K., Hayashi, K., and Minoda, A. (2021) UniverSC: a flexible cross-platform single-cell data processing pipeline. bioRxiv 2021.01.19.427209; doi: https://doi.org/10.1101/2021.01.19.427209 package version 1.0.3. https://github.com/minoda-lab/universc
@article {Kelly2021.01.19.427209,
author = {Kelly, S. Thomas and Battenberg, Kai and Hetherington, Nicola A. and Hayashi, Makoto and Minoda, Aki},
title = {{UniverSC}: a flexible cross-platform single-cell data processing pipeline},
elocation-id = {2021.01.19.427209},
year = {2021},
doi = {10.1101/2021.01.19.427209},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Single-cell RNA-sequencing analysis to quantify RNA molecules in individual cells has become popular owing to the large amount of information one can obtain from each experiment. We have developed UniverSC (https://github.com/minoda-lab/universc), a universal single-cell processing tool that supports any UMI-based platform. Our command-line tool enables consistent and comprehensive integration, comparison, and evaluation across data generated from a wide range of platforms.Competing Interest StatementThe authors have declared no competing interest.},
eprint = {https://www.biorxiv.org/content/early/2021/01/19/2021.01.19.427209.full.pdf},
journal = {{bioRxiv}},
note = {package version 1.0.3},
URL = {https://github.com/minoda-lab/universc},
}
@Manual{,
title = {{UniverSC}: a flexible cross-platform single-cell data processing pipeline},
author = {S. Thomas Kelly, Kai Battenberg, Nicola A. Hetherington, Makoto Hayashi, and Aki Minoda},
year = {2021},
note = {package version 1.0.3},
url = {https://github.com/minoda-lab/universc},
}
To add further support for other technologies or troubleshoot problems, please submit an Issue to the GitHub repository: https://github.com/TomKellyGenetics/universc/issues
Please submit issues on GitHub to report
problems or suggest features. Pull requests
to the dev branch on GitHub are also welcome to add features or correct problems. Please see
the contributor guide for more details.
Where possible, please provide an minimal example of the first few lines of each FASTQ file for testing purposes.
It is also helpful to describe the technology, such as:
- length of barcode
- length of UMI
- which reads they're on
- whether there is a known barcode whitelist available
- whether adapters or linkers are required
- whether a preprint, publication, or company specifications are available
Technologies that may be difficult to support are those with:
- barcodes longer than 16bp (only up to 16bp at the end will be used with the rest trimmed off)
- UMIs longer than 12bp (only upto 12bp at the begging will be used with the rest trimmed off)
- barcodes longer or varying length
- combinatorial indexing
- dual indexing
Please bear this in mind when submitting requests. We will consider to add further technologies but it could take significant resources to add support for these.
This script requires Cell Ranger to be installed and exported to the PATH (version 3.0.0 or higher recommended). The script itself is exectuable and does not require installation to run but you can put it in your PATH or bin of your Cell Ranger install if you wish to do so. We provide scripts to do this for your convenience.
See the details below on how set up Cell Ranger and launch_universc.sh.
To download UniverSC open a terminal prompt and enter the following commands.
cd $HOME/Downloads
git clone https://github.com/TomKellyGenetics/universc.git
cd universc
If you already have Cell Ranger installed, then you can run the script without installing it.
bash launch_universc.sh
You can call it in another directory by giving the path to the script.
cd $/HOME/my_project
bash $HOME/Downloads/universc/launch_universc.sh
See the details below on how to install Cell Ranger and launch_universc.sh add them
to the PATH so that launch_universc.sh can be run from any directory.
If you are running code in a git repository you can add UniverSC as a submodule.
cd $/HOME/my_git_repo
git submodule add https://github.com/TomKellyGenetics/universc.git
bash universc/launch_universc.sh
In principle, the script can run on any Unix systems with Cell Ranger installed. You can check whether Cell Ranger is already availble by running:
whereis cellranger
You can see which Cell Ranger installation will run as follows:
which cellranger
cellranger count --version
If Cell Ranger is already installed on your system, you can add it to your $PATH as follows:
export PATH=/home/username/path/to/cellranger-x.x.x:$PATH
If Cell Ranger is not installed on your system, you must install it before running launch_universc.sh.
Please see the manual for Cell Ranger on the 10x Genomics website for more details on how to use it. We provide support for passing various options to Cell Ranger and sensible defaults for each technology.
This script is compatible with the installation of Cell Ranger that you can download from the 10x Genomics website and gives the same output formats.
However, we recommend to use the open-source release of Cell Ranger on GitHub. This is release on an MIT License and is not subject to the 10x Genomics End User License Agreement.
We provide open-source repositories with minor updates for compatibility with current versions of dependencies.
The code is available here:
https://github.com/TomKellyGenetics/cellranger/releases
We also provide Docker images for Cell Ranger versions 2.0.2, 2.1.0, 2.1.1, and 3.0.2:
https://github.com/TomKellyGenetics/cellranger_clean/packages
https://hub.docker.com/r/tomkellygenetics/cellranger_clean/tags
These have been pre-installed in the Docker image described above.
A full example of installation is available in the GitHub repository and on DockerHub.
- Python 2.7.13
- rust 1.28.0
- clang 6.0
- go 1.11
- node 8.11.4
- Cython 0.28.0
- STAR 2.5.1b
- bcl2fastq 2.19.1.403
- tsne 0.15
The following additional shell utilities are required. Mac OS and most Linux distributions come with these pre-installed.
- make 3.81
- git 2.20.1
- sed (GNU sed) 4.4 (gsed)
- tar 2.8.3
- rename 0.20 (perl-rename)
- perl 5.26.1
- rsync 2.6.9
Note that rename is installed by default on Mac, Ubuntu and Debian but a different version must be used on other Linux distrubutions.
CentOS and Fedora:
sudo yum install prename
sudo dnf install prename
Red Hat Linux:
sudo rpm install prename
Arch Linux:
yay perl-rename
- git-lfs 2.10.0
- 8-core Intel or AMD processor (16 cores recommended)
- 64GB RAM (128GB recommended)
- 1TB free disk space
- 64-bit CentOS/RedHat 6.0 or Ubuntu 12.04
The conversion process requires write-access to to the Cell Ranger install directory so an install on your user directory is recommended.
You can check where Cell Ranger is installed with:
which cellranger
If calling the script gives the help menu, launch_universc.sh has sucessfully run with access to the directories that it needs. It will give an error message if the Cell Ranger directory is not writeable.
bash launch_universc.sh
This script requires Cell Ranger (version 3.0.0 or higher recommended) to be installed and have write-access to the Cell Ranger install directory, so an install on your user directory is recommended. This script also requires Cell Ranger to be exported to the PATH. The script itself is exectuable and does not require installation to run but you can put it in your PATH or bin of your Cell Ranger install if you wish to do so.
This script will run in bash on any OS (but it has only been tested on Linux Debian). Running Cell Ranger with this configuration requires a lot of memory (40Gb) so running on server is recommended. SGE job modes are supported to run Cell Ranger with multiple threads.
This is required because launch_universc.sh will make changes to the Cell Ranger install to ensure compatibility with the technology running. A local install in you user home directory is needed to make these changes. This ensures that these changes do not affect jobs run by other users and allows launch_universc.sh to change the whitelist and source code as needed.
These changes are reversible but mean that only one technology can be run at the same time. You can restore original configurations with:
bash launch_universc.sh -t "10x" --setup
If Cell Ranger is not already installed we recommend installing it in a directory that
you have write access to such as $HOME/local.
If Cell Ranger has been installed by a system administrator, you will only have read-access to that installation. You can still use rather than installing a new version but you will need to copy it to your home directory and add this version to your PATH.
mkdir -p $HOME/local
cd ~/local
installed_version=$(echo $(which cellranger) | rev | cut -d"/" -f2- | rev)
cp -rv $installed_version .
installed_directory=$(echo $(which cellranger) | rev | cut -d"/" -f2 | rev)
cd $installed_directory
new_version=$(pwd)
#remove previous version from PATH
export PATH=$(echo $PATH | sed "s;$installed_version:;;g")
#add new version to PATH
eval $(echo export PATH=$new_version:\$PATH)
cd ..
You should be able to see that the locally installed version can be called as follows:
echo $PATH
which cellranger
bash launch_universc.sh
Adding the script to the PATH is not absolutely neccessary, it can be called as follows from the directory that it is downloaded in.
cd $HOME/Downloads
git clone https://github.com/TomKellyGenetics/universc.git
cd universc
bash launch_universc.sh
We provide a Makefile with all necessary configurations to automatically check whether launch_universc.sh is installed correctly.
You can specify any directory to install as a "prefix". This will create a directory "$HOME/local/universc-0.3" where the files needed will be stored.
cd $HOME/Downloads
git clone https://github.com/TomKellyGenetics/universc.git
make
make install prefix=$HOME/local
It is also possible to add the current working directory as the installed directory.
make install prefix="."
In this case do not delete the installed directory after you install it or the script will fail to run.
By default it will be installed in a root directory with read-only access. This requires administrator priviledges. Note that the manual can onlly be installed with root priviledges.
sudo make install
sudo make manual
You can verify that launch_universc.sh has been added to the PATH.
echo $PATH
which launch_universc.sh
You can then run launch_universc.sh from any working directory.
If launch_universc.sh is already installed and you wish to update it, first you need to pull the changes from GitHub from the universc directory.
cd universc
git pull origin master
make
Then you can update to the directory of your choice using
the same options for --prefix as to install.
make install prefix=$HOME/local
This is remove previous versions of launch_universc.sh and install the latest version.
The manual can be updated with:
sudo make manual
Before uninstalling UniverSC please ensure that any versions of Cell Ranger used are restored to their default configuration:
export PATH=/Users/tom/Downloads/cellranger-x.y.z:$PATH
bash launch_universc.sh -t "10x" --setup
We provide an automated script to reverse the changes above.
make uninstall
This is will automatically detect the installation of launch_universc.sh.
If multiple versions of Cell Ranger are present, you can specify which to remove with.
make remove prefix=$HOME/local
Make will install the script with bash by default but
alternative shells are supported. You will need to run the
install script or run it with your shell of choice.
sh launch_universc.sh
sh inst/INSTALL --prefix $HOME/local
launch_universc.sh
ksh launch_universc.sh
ksh inst/INSTALL --prefix $HOME/local
launch_universc.sh
zsh launch_universc.sh
zsh inst/INSTALL --prefix $HOME/local
launch_universc.sh
fish launch_universc.sh
fish inst/INSTALL --prefix $HOME/local
launch_universc.sh
The help menu should reflect the shell used to run it.
To update, similarly run the inst/UPGRADE script with
your chosen shell.
We provide a docker image with all software needed to run UniverSC.
This requires "docker" to be installed and a valid DockerHub account.
You can check whether docker is available by running:
which docker
docker run hello-world
This may require you to login to your account.
docker login -u "myusername"
If you cannot run docker on a remote server, contact your systems administrator.
We provide a docker image for UniverSC version 1.0.3.
You can import it if you have docker installed.
docker pull tomkellygenetics/universc:latest
Then you can run convert with:
run -it tomkellygenetics/universc:latest launch_universc.sh
You can open a shell in the docker image with:
run -it tomkellygenetics/universc:latest /bin/bash
run -it tomkellygenetics/universc:latest /bin/zsh
Either of these shells are supported.
The Dockerfile is provided in the repository so it can be built from source. This will build a Docker image with the latest version of universc provided that updates to dependencies on GitHub are still compatible.
git clone https://github.com/TomKellyGenetics/universc.git
docker build -t universc:latest .
Please bear mind that it can take considerable time to install all necessary dependencies. A stable internet connection is required.
You can manually add the script here to the PATH, for example:
PATH=$HOME/Downloads/universc:$PATH
This means that the directory where the script is can be found from the shell.
echo $PATH
cd ~
launch_universc.sh
Add the following line to the ~/.bashrc file and use source ~/.bashrc
to load a new session. This means that you do not need to add the
sript to the PATH in future sessions.
export PATH=$HOME/Downloads/universc:$PATH
This repository comes with almost all necessary files to run test jobs. Test data and Cell Ranger references are available with Git large file storage (LFS).
To install git LFS run:
curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
sudo apt-get install git-lfs
git lfs install
To import large files from Github change to the "universc" directory and run:
git lfs pull origin
This provides almost all files required. The STAR index and reference need to be generated or imported from an existing reference. The following code detects whether the references are available in an existing cellranger installation.
cellrangerversion=`cellranger count --version | head -n 2 | tail -n 1 | cut -f2 -d'(' | cut -f1 -d')'`
cellrangerpath=`which cellranger`
# set up cellranger reference
if [[ ! -f test/cellranger_reference/cellranger-tiny-ref/3.0.0/star/SA ]] && [[ -f $(dirname $cellrangerpath)/cellranger-tiny-ref/3.0.0/star/SA ]]; then
rsync $(dirname $cellrangerpath)/cellranger-tiny-ref/3.0.0/star/SA test/cellranger_reference/cellranger-tiny-ref/3.0.0/star/SA
fi
if [[ ! -f test/cellranger_reference/cellranger-tiny-ref/1.2.0/star/SA ]] && [[ -f $(dirname $cellrangerpath)/cellranger-tiny-ref/1.2.0/star/SA ]]; then
rsync $(dirname $cellrangerpath)/cellranger-tiny-ref/1.2.0/star/SA test/cellranger_reference/cellranger-tiny-ref/1.2.0/star/SA
fi
This creates a reference for Cell Ranger here:
-
test/cellranger_reference/cellranger-tiny-ref/1.2.0
-
test/cellranger_reference/cellranger-tiny-ref/3.0.0
You can reset the references with the automated settings here:
cd test/cellranger_reference/cellranger-tiny-ref/
make clean
make reference
cd ../../..
It is also possible to generate a custom reference for any genome provided you have a FASTQ genome reference file and a GTF/GFF3 annotation file. Please ensure that the chromosomes match between the FASTA headers and the chromosome column (1st) of the GTF/GFF3 file.
The gffread function includes with the cufflinks
utility can convert to gtf. For example:
gffread test/cellranger_reference/cellranger-tiny-ref/genes-1.2.0.gff3 -T -o test/cellranger_reference/cellranger-tiny-ref/genes-1.2.0.gtf
To generate new references we first remove the references imported.
rm -rf test/cellranger_reference/cellranger-tiny-ref/1.2.0 test/cellranger_reference/cellranger-tiny-ref/3.0.0
We then generate references from the FASTA and GTF files as shown in the following examples:
cellranger mkref --genome=test/cellranger_reference/cellranger-tiny-ref/1.2.0 \
--fasta=test/cellranger_reference/cellranger-tiny-ref/genome-1.2.0.fa \
--genes=test/cellranger_reference/cellranger-tiny-ref/ genes-1.2.0.gtf
cellranger mkref --genome=test/cellranger_reference/cellranger-tiny-ref/3.0.0 \
--fasta=test/cellranger_reference/cellranger-tiny-ref/genome-3.0.0.fa \
--genes=test/cellranger_reference/cellranger-tiny-ref/ genes-3.0.0.gtf
See the Cell Ranger manuals for more details on references.
The script will:
- give you a help guide
bash launch_universc.sh -h
-
convert R1 files so that barcodes and UMIs are where they're expected to be for 10x (this can take some time for larger files)
-
runs Cell Ranger with the same parameters as for 10x and treats samples exactly the same
-
the barcode whitelists are changed and some checks on barcodes disabled (requires a writeable install of Cell Ranger in your user directory)
-
it can run Cell Ranger in parallel in SGE mode on the server if you use
--jobmode "sge"and set up ansge.templatefile -
it can also restore the original Cell Ranger settings for running 10x samples
bash launch_universc.sh --setup --technology "10x"
Please note that this script alters the barcode whitelist. Known ICELL8 barcodes are supported but this is not possible with Nadia or DropSeq chemistry so 100% valid barcodes will be returned.
You can display a manual from the locally installed UniverSC directory with:
man man/launch_universc.sh
Note that the working directory must be universc or the full path to the man directory must be given.
We provide an automated script to install the manual.
sudo make manual
You can remove the manual with:
sudo make manual-clean
The manual can be installed as follows on Mac and Linux.
# add manual directory to PATH if not already found
## check config for Linux
if [[ -f /etc/manpath.config ]]
then CONFIG="/etc/manpath.config"
fi
## check config for Mac
if [[ -f /etc/manpaths ]]
then CONFIG="/etc/manpaths"
fi
if [[ ! -z $CONFIG ]]
then MANDIR=`tail -n 1 ${CONFIG}`
else if [[ ! -z $MANPATH ]]
then
SHELL_RC=`echo ~/.${0}rc`
echo "export MANPATH=/usr/local/man" >> $SHELL_RC
MANDIR=`echo ${MANPATH} | cut -d: -f1`
fi
fi
sudo mkdir -p ${MANDIR}/man1
cp man/launch_universc.sh man/launch_universc.sh.1
sudo mv man/launch_universc.sh.1 ${MANDIR}/man1/launch_universc.sh.1
gzip ${MANDIR}/man1/launch_universc.sh.1
Alternatively the man can be installed with:
cp man/launch_universc.sh man/launch_universc.sh.1
sudo install -g 0 -o 0 -m 0644 man/launch_universc.sh.1 ${MANDIR}/man1
The manual can then be called from any directory as follows:
man launch_universc.sh
You can access the following help menu with launch_universc.sh --help in the terminal.
Usage:
bash launch_universc.sh --testrun -t THECHNOLOGY
bash launch_universc.sh -t TECHNOLOGY --setup
bash launch_universc.sh -R1 FILE1 -R2 FILE2 -t TECHNOLOGY -i ID -r REFERENCE [--option OPT]
bash launch_universc.sh -R1 READ1_LANE1 READ1_LANE2 -R2 READ2_LANE1 READ2_LANE2 -t TECHNOLOGY -i ID -r REFERENCE [--option OPT]
bash launch_universc.sh -f SAMPLE_LANE -t TECHNOLOGY -i ID -r REFERENCE [--option OPT]
bash launch_universc.sh -f SAMPLE_LANE1 SAMPLE_LANE2 -t TECHNOLOGY -i ID -r REFERENCE [--option OPT]
bash launch_universc.sh -v
bash launch_universc.sh -h
Convert sequencing data (FASTQ) from Nadia or ICELL8 platforms for compatibility with 10x Genomics and run cellranger count
Mandatory arguments to long options are mandatory for short options too.
--testrun Initiates a test trun with the test dataset
-R1, --read1 FILE Read 1 FASTQ file to pass to Cell Ranger (cell barcodes and umi)
-R2, --read2 FILE Read 2 FASTQ file to pass to Cell Ranger
-I1, --index1 FILE Index (I1) FASTQ file to pass to Cell Ranger (OPTIONAL)
-I2, --index2 FILE Index (I2) FASTQ file to pass to Cell Ranger (OPTIONAL and EXPERIMENTAL)
-f, --file NAME Path and the name of FASTQ files to pass to Cell Ranger (prefix before R1 or R2)
e.g. /path/to/files/Example_S1_L001
-i, --id ID A unique run id, used to name output folder
-d, --description TEXT Sample description to embed in output files.
-r, --reference DIR Path of directory containing 10x-compatible reference.
-t, --technology PLATFORM Name of technology used to generate data.
Supported technologies:
10x Genomics (version automatically detected): 10x, chromium
10x Genomics version 2 (16bp barcode, 10bp UMI): 10x-v2, chromium-v2
10x Genomics version 3 (16bp barcode, 12bp UMI): 10x-v3, chromium-v3
CEL-Seq (8bp barcode, 4bp UMI): celseq
CEL-Seq2 (6bp UMI, 6bp barcode): celseq2
Drop-Seq (12bp barcode, 8bp UMI): nadia, dropseq
ICELL8 version 3 (11bp barcode, 14bp UMI): icell8 or custom
inDrops version 1 (19bp barcode, 6bp UMI): indrops-v1, 1cellbio-v1
inDrops version 2 (19bp barcode, 6bp UMI): indrops-v2, 1cellbio-v2
inDrops version 3 (16bp barcode, 6bp UMI): indrops-v3, 1cellbio-v3
MARS-Seq (6bp barcode, 10bp UMI): marsseq, marsseq-v1
MARS-Seq2 (7bp barcode, 8bp UMI): marsseq2, marsseq-v2
Quartz-Seq2 (14bp barcode, 8bp UMI): quartzseq2-384
Quartz-Seq2 (15bp barcode, 8bp UMI): quartzseq2-1536
SCI-Seq 2-level indexing (30 bp barcode, 8 bp UMI): sciseq2
SCI-Seq 3-level indexing (40 bp barcode, 8 bp UMI): sciseq3
SCRB-Seq (6bp barcode, 10bp UMI): scrbseq, mcscrbseq
SeqWell (12bp barcode, 8bp UMI): seqwell
Smart-seq, Smart-seq2 (16bp barcode, No UMI): smartseq2
Smart-seq2-UMI, Smart-seq3 (16bp barcode, 8bp UMI): smartseq3
SPLiT-Seq (10bp UMI, 18bp barcode): splitseq
SPLiT-Seq2 (10bp UMI, 24bp barcode): splitseq2
SureCell (18bp barcode, 8bp UMI): surecell, ddseq, biorad
Custom inputs are also supported by giving the name "custom" and length of barcode and UMI separated by "_"
e.g. Custom (16bp barcode, 10bp UMI): custom_16_10
Experimental
Microwell-Seq (18 bp barcode, 6 bp UMI): microwell
BD Rhapsody (27 bp barcode, 8 bp UMI): bd-rhapsody
STRT-Seq (6 bp barcode, no UMI)
STRT-Seq-C1 (8 bp barode, 5 bp UMI)
STRT-Seq-2i (13 bp barcode, 6 bp UMI)
SmartSeq2 (16 bp barcode, no UMI)
-b, --barcodefile FILE Custom barcode list in plain text (with each line containing a barcode)
-c, --chemistry CHEM Assay configuration, autodetection is not possible for converted files: SC3Pv2 (default), SC5P-PE, or SC5P-R2
-n, --force-cells NUM Force pipeline to use this number of cells, bypassing the cell detection algorithm.
-j, --jobmode MODE Job manager to use. Valid options: local (default), sge, lsf, or a .template file
--localcores NUM Set max cores the pipeline may request at one time.
Only applies when --jobmode=local.
--localmem NUM Set max GB the pipeline may request at one time.
Only applies when --jobmode=local.
--mempercore NUM Set max GB each job may use at one time.
Only applies in cluster jobmodes.
-p, --per-cell-data Generates a file with basic run statistics along with per-cell data
--setup Set up whitelists for compatibility with new technology and exit
--as-is Skips the FASTQ file conversion if the file already exists
-h, --help Display this help and exit
-v, --version Output version information and exit
--verbose Print additional outputs for debugging
For each fastq file, follow the naming convention below:
<SampleName>_<SampleNumber>_<LaneNumber>_<ReadNumber>_001.fastq
e.g. EXAMPLE_S1_L001_R1_001.fastq
Example_S4_L002_R2_001.fastq.gz
For custom barcode and umi length, follow the format below:
custom_<barcode>_<UMI>
e.g. custom_16_10 (which is the same as 10x)
Files will be renamed if they do not follow this format. File extension will be detected automatically.
cellranger testrun --id="tiny-test"
# open gzip files from test data
gunzip -fk universc/test/shared/cellranger-tiny-fastq/3.0.0/*fastq.gz
gunzip -fk cellranger-3.0.2.9001/cellranger-cs/3.0.2.9001/lib/python/cellranger/barcodes/3M-february-2018.txt.gz
# Cell Ranger call
cellranger count --id="tiny-count-v3" \
--fastqs="cellranger-3.0.2.9001/cellranger-tiny-fastq/3.0.0/" --sample="tinygex" \
--transcriptome="cellranger-3.0.2.9001/cellranger-tiny-ref/3.0.0"
# call convert on 10x with multiple lanes
bash /universc/launch_universc.sh --id "test-10x-v3" --technology "10x" \
--reference "/universc/test/cellranger_reference/cellranger-tiny-ref/3.0.0" \
--file "/universc/test/shared/cellranger-tiny-fastq/3.0.0/tinygex_S1_L001" \
"/universc/test/shared/cellranger-tiny-fastq/3.0.0/tinygex_S1_L002"
Obtain DropSeq data from public database:
wget https://www.ncbi.nlm.nih.gov/geo/download/\?acc\=GSM1629192\&format\=file\&file\=GSM1629192%5FPure%5FHumanMouse%2Ebam
mv index.html\?acc=GSM1629192\&format=file\&file=GSM1629192%5FPure%5FHumanMouse%2Ebam GSM162919.bam
samtools sort -n GSM162919.bam > GSM162919.qsort
samtools view GSM162919.qsort HUMAN_21:9825832-48085036 > GSM162919.qsort2
samtools sort -O BAM GSM162919.bam > GSM162919.sort.bam
samtools index GSM162919.sort.bam
samtools view GSM162919.sort.bam HUMAN_21:9825832-48085036 > GSM162919.chr21.bam
samtools view -O BAM GSM162919.sort.bam HUMAN_21:9825832-48085036 > GSM162919.chr21.sort.bam
samtools sort -n GSM162919.chr21.sort.bam -o GSM162919.chr21.qsort.bam
bedtools bamtofastq -i GSM162919.chr21.qsort.bam -fq GSM1629192_chr21_R1.fastq
mv GSM1629192_chr21_R1.fastq GSM1629192_chr21_R2.fastq
fastq-dump -F --split-files SRR1873277
fastq_pair GSM1629192_chr21_R2.fastq SRR1873277_1.fastq
head -n 117060 SRR1873277_1.fastq.paired.fq 117060 > SRR1873277_1.fastq.paired.fq
head -n 117060 GSM1629192_chr21_R2.fastq.paired.fq > GSM1629192_chr21_R2.fastq.paired.fq
cp SRR1873277_1.fastq.paired.fq GSM1629192_chr21_R2.fastq.paired.fq ~/repos/universc/test/shared/dropseq-test
cp SRR1873277_1.fastq.paired.fq GSM1629192_chr21_R2.fastq.paired.fq ~/repos/universc/test/shared/dropseq-test
mv SRR1873277_1.fastq.paired.fq SRR1873277_R1.fastq
mv GSM1629192_chr21_R2.fastq.paired.fq universc/test/shared/dropseq-test/SRR1873277_R2.fastq
mv GSM1629192_chr21_R2.fastq.paired.fq universc/test/shared/dropseq-test/SRR1873277_R2.fastq
Run UniverSC:
bash universc/launch_universc.sh -t "DropSeq" --setup
# call on dropseq with files
bash universc/launch_universc.sh --id "test-dropseq" --technology "nadia" \
--reference "universc/test/cellranger_reference/cellranger-tiny-ref/3.0.0" \
--read1 "universc/test/shared/dropseq-test/SRR1873277_S1_L001_R1_001" \
--read2 "universc/test/shared/dropseq-test/SRR1873277_S1_L001_R2_001"
# call on icell8 files with custom whitelist and non-standard file names
bash launch_universc.sh --setup -t "icell8" --barcodefile "test/shared/icell8-test/BarcodeList.txt"
bash launch_universc.sh --id "test-icell8-custom" --technology "iCell8" \
--reference "test/cellranger_reference/cellranger-tiny-ref/3.0.0" \
--read1 "test/shared/icell8-test/iCELL8_01_S1_L001_R1_001.fastq" "test/shared/icell8-test/iCELL8_01_S1_L002_R1_001.fastq" \
--read2 "test/shared/icell8-test/iCELL8_01_S1_L001_R2_001.fastq" "test/shared/icell8-test/iCELL8_01_S1_L002_R2_001.fastq" \
--barcodefile "test/shared/icell8-test/BarcodeList.txt" \
--jobmode "sge"
We've made considerable efforts to ensure you don't run into problems. However, it may be necessary from time to time to troubleshoot issues calling UniverSC. For other technologies, various changes to Cell Ranger are made in a reversible fashion. If you run into problems you can restore Cell Ranger to default parameters:
bash launch_universc.sh -t "10x" --setup
Then you can call launch_universc.sh as above or configure Cell Ranger for your technology of choice such as :
bash launch_universc.sh --setup -t "icell8" --barcodefile "test/shared/icell8-test/BarcodeList.txt"
Set up calls are particularly useful to set up the whitelist in advance of running multiple samples simultaneously, provided they are the same technology.
It is also possible that your Cell Ranger installation will be "locked" by UniverSC. This is intentional to prevent different technologies running simultaneously. When running Cell Ranger, we need to ensure that the barcode whitelist corresponds to the technology that is running and cannot be changed until existing runs will finish.
However, this means that in the case of an error or if a job is "killed", then the lock file will not be cleared. You can do this manually as follows:
cellrangerversion=`cellranger count --version | head -n 2 | tail -n 1 | cut -f2 -d'(' | cut -f1 -d')'`
cellrangerpath=`which cellranger`
rm ${cellrangerpath}-cs/${cellrangerversion}/lib/python/cellranger/barcodes/.lock
When doing this please ensure that no other instances are running for Cell Ranger convert.
You can also see the current configuration of UniverSC for each Cell Ranger install as follows:
cellrangerversion=`cellranger count --version | head -n 2 | tail -n 1 | cut -f2 -d'(' | cut -f1 -d')'`
cellrangerpath=`which cellranger`
cat ${cellrangerpath}-cs/${cellrangerversion}/lib/python/cellranger/barcodes/.lastcalled
These columns show the barcode length, UMI length, and barcode whitelist of the last technology used by UniverSC. Please do not remove this file unless the last technology used is 10x Genomics.
This package is provided open-source on a GPL-3 license. This means that you are free to use and modify this code provided that they also contain this license.
Please note that we are third-party developers releasing it for use by users like ourselves. We are not affiliated with 10x Genomics, Dolomite Bio, Takara Bio, or any other vendor of single-cell technologies. This software is not supported by 10x Genomics and only changes data formats so that other technologies can be used with the Cell Ranger pipeline.
Cell Ranger (version 2.0.2, 2.1.0, 2.1.0, and 3.0.2) has been released open source on and MIT license on GitHub. We use this version of Cell Ranger for testing and running our tools. Note that the code that generates the 'cloupe' files is not included in this release. The Cloupe browser uses files generated by proprietary closed-source software and is subject to the 10x Genomics End-User License Agreement which does not allow use with data generated from other platforms.
Therefore 'launch_universc.sh' does not support Cloupe files and you should not use them with technologies other than 10x Genomics.