bbi-sciatac-demux implements Andrew Hill's sci-ATAC-seq demultiplexing processing pipeline and bbi-sciatac-analyze implements his sci-ATAC-seq analysis pipeline in the Nextflow domain-specific language.

In order to run these pipeline scripts, Nextflow must be installed on the system where they will run. You can find Nextflow installation instructions on the Nextflow web site. These scripts require Nextflow version >= 20.07.1 and <= 22.10.4.

These scripts are written to run on the UW Genome Sciences computing cluster: they depend on the Univa Grid Engine and various installed modules.

Install the scripts using the git program to clone the bbi-lab/bbi-sciatac-demux and bbi-lab/bbi-sciatac-analyze repositories on your computer. Use the commands

git clone https://github.com/bbi-lab/bbi-sciatac-demux
git clone https://github.com/bbi-lab/bbi-sciatac-analyze

For efficiency and convenience, they are written to run certain stages in python virtual environments. The environments may need to be built on a node with the CPU architecture on which you will run the scripts. There are additional details in the create_virtual_envs.sh script. In order to build the environments use the commands

qlogin -l mfree=16G

cd bbi-sciatac-demux
bash create_virtual_envs.sh
cd ..

cd bbi-sciatac-analyze
bash create_virtual_envs.sh
cd ..

The above is a one-time installation setup, or may be required if you need to update the environment.

The bbi-sciatac-analyze pipeline uses two compiled programs to find and process hash reads for sciPlex experiments. These programs require a Rust compiler, which is installed using the information at

https://www.rust-lang.org/tools/install

After installing the Rust compiler, build and install the programs by running the script bbi-sciatac-analyze/install_rust_programs.sh.

In addition, a python3 interpreter is required.

Nextflow is both a language specification for writing scientific processing pipeline scripts and a program for running such scripts. Important features offered by Nextflow include support for distributed computing on the Univa Grid Engine and the ability to resume processing at a failed processing stage.

The Nextflow pipeline components required for the bbi-sciatac pipelines consist of the

• nextflow program, the executable in the Nextflow distribution,
• nextflow.config file, gives processing parameters, for example, for the Univa Grid Engine,
• params.config file, gives parameters for a particular processing run,
• samplesheet.json file, gives information about the samples in the sequencing run,
• work directory, where Nextflow 'stages' the processing steps. In particular, files created during the processing are stored in sub-directories of work,
• genome file sets,
• computing resources.

The bbi-sciatac pipelines consist of a pair of Nextflow scripts. The first script, bbi-sciatac-demux/main.nf, converts Illumina bcl files to fastq files, corrects barcode errors, partitions reads into fastq files by sample, and trims off adapter sequence from the reads. The second script, bbi-sciatac-analyze/main.nf, continues processing with read alignments.

The user-generated samplesheet file (front-end samplesheet) is in CSV format. The program bbi-sciatac-demux/samplesheet/sciatac_samplesheet.py converts this file to a JSON file (back-end samplesheet), which is required by the pipeline. In addition, the user can set various processing parameters using sciatac_samplesheet.py command line parameters. For additional information about sciatac_samplesheet.py, including a detailed description of the front-end samplesheet format, run

sciatac_samplesheet.py -d

In order to process a sciPlex experiment, run the samplesheet conversion program, bbi-sciatac-demux/samplesheet/sciatac_samplesheet.py with the --hash_file command line option. The --hash_file option takes the full path to the hash index file, and enables hash read processing in the bbi-sciatac-analyze pipeline.

The required genome-related files are specified in the bbi-sciatac-analyze/genomes.json file. The file genomes_format.txt in the bbi-sciatac-analyze/genomes directory describes the genomes.json file format. This description is from Andrew Hill.

The nextflow.config file defines processing values such as the required modules, memory, and number of CPUs for each processing stage, which do not change typically from run-to-run. The file can be left in the bbi-sciatac-* installation directory where Nextflow searches for it automatically when a pipeline run starts. The supplied nextflow.config file has two profiles: the default profile, called standard, defines modules used by the pipeline on Ubuntu 22.04 systems in the UW Genome Sciences cluster, and the centos7 profile, which defines modules used by the pipeline on CentOS 7 systems in the UW Genome Sciences cluster. In order to run the pipelines with the centos7 profile, add the command line parameter -profile centos7 to the nextflow run command, for example

nextflow run bbi-dmux -profile centos7 -c experiment.config

This nextflow.config file has comments that give additional information.

The lines in the experiment.config file define parameters required by the processing pipeline, such as the Illumina run directory and the processing pipeline output directory. There is additional information in the example experiment.config files in the pipeline repositories.

Run the pipeline scripts in a cluster node a significant memory resource. For example, use

qlogin -l mfree=16G

Copy the experiment.config file and bash scripts bbi-sciatac-demux/scripts/run.sciatac-demux.sh and bbi-sciatac-analyze/scripts/run.sciatac-analyze.sh to the directory where you want the pipeline output files. Edit run.sciatac-demux.sh and n.sciatac-analyze.shas described in the script comments. Edit experiment.config as required then run run.sciatac-demux.sh followed by run.sciatac-analyze.sh.

bash run.sciatac-demux.sh
.
.
.
bash run.sciatac-analyze.sh

Each script starts by reporting important parameters and then waits run confirmation.

The script run.sciatac-demux.sh creates a sub-directory called demux_out where the demux pipeline writes its output files. The run.sciatac-analyze.sh script creates a sub-directory called analyze_out where the analyze pipeline writes its output files.

We advise users to run the pipelines in tmux sessions so that closing the terminal window does not terminate the pipeline.

When run with the -with-trace <trace_file_name> command line parameter, Nextflow writes helpful information to a trace file. In the case that Nextflow is run on a Grid Engine, the trace file has a column labelled native_id, which is the Grid Engine job id. You can use this job id with the qacct -j <job_id> Grid Engine command to better understand why the Grid Engine may have killed a process. Additionally, the trace file has columns with the amount of memory used by each process and process hash strings, which you can use to tune the Grid Engine memory requests and find the corresponding process sub-directory in the Nextflow work directory, respectively.

If you run into problems, please leave a detailed description in the issue tab above.

A debt of gratitude is due to the many members of the Shendure and Trapnell labs as well as the BBI team who have worked on portions of this pipeline or its predecessors, especially Hannah Pliner, Aishwarya Gogate, Andrew Hill, and Jonathan Packer.