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A bioinformatics pipeline based on Ruffus

Author: Bernie Pope (bjpope@unimelb.edu.au)

Crpipe is based on the Ruffus library for writing bioinformatics pipelines. Its features include:

  • Job submission on a cluster using DRMAA (currently only tested with SLURM).
  • Job dependency calculation and checkpointing.
  • Pipeline can be displayed as a flowchart.
  • Re-running a pipeline will start from the most up-to-date stage. It will not redo previously completed tasks.

License

3 Clause BSD License. See LICENSE.txt in source repository.

Installation

External dependencies

crpipe depends on the following programs and libraries:

  • python (version 2.7.5)
  • DRMAA for submitting jobs to the cluster (it uses the Python wrapper to do this). You need to install your own libdrama.so for your local job submission system. There are versions available for common schedulers such as Torque/PBS, SLURM and so on.
  • fastqc (version 0.10.1)
  • samtools version 1.1)
  • bwa for aligning reads to the reference genome (version 0.7.12)
  • sambamba for sorting bam files (version 0.5.4).
  • lumpy for calling structural variants (version 0.2.11)
  • svtyper for genotyping the structural variants (version 0.0.2)

You will need to install these dependencies yourself.

I recommend using a virtual environment:

cd /place/to/install
virtualenv crpipe
source crpipe/bin/activate
pip install -U https://github.com/bjpop/crpipe

If you don't want to use a virtual environment then you can just install with pip:

pip install -U https://github.com/bjpop/crpipe

Worked example

The example directory in the source distribution contains a small dataset to illustrate the use of the pipeline.

Get a copy of the source distribution

cd /path/to/test/directory
git clone https://github.com/bjpop/crpipe

Install crpipe as described above

Get a reference genome.

cd crpipe/example
mkdir reference
# copy your reference into this directory, or make a symbolic link
# call it reference/genome.fa

Tell Python where your DRMAA library is

For example (this will depend on your local settings):

export DRMAA_LIBRARY_PATH=/usr/local/slurm_drmaa/1.0.7-gcc/lib/libdrmaa.so

Run crpipe and ask it what it will do next

crpipe -n --verbose 3

Generate a flowchart diagram

crpipe --flowchart pipeline_flow.png --flowchart_format png

Run the pipeline

crpipe --use_threads --log_file pipeline.log --jobs 2 --verbose 3

Usage

You can get a summary of the command line arguments like so:

crpipe -h
usage: crpipe [-h] [--verbose [VERBOSE]] [-L FILE] [-T JOBNAME] [-j N]
              [--use_threads] [-n] [--touch_files_only] [--recreate_database]
              [--checksum_file_name FILE] [--flowchart FILE]
              [--key_legend_in_graph] [--draw_graph_horizontally]
              [--flowchart_format FORMAT] [--forced_tasks JOBNAME]
              [--config CONFIG] [--jobscripts JOBSCRIPTS] [--version]

Colorectal cancer pipeline

optional arguments:
  -h, --help            show this help message and exit
  --config CONFIG       Pipeline configuration file in YAML format, defaults
                        to pipeline.config
  --jobscripts JOBSCRIPTS
                        Directory to store cluster job scripts created by the
                        pipeline, defaults to jobscripts
  --version             show program's version number and exit

Common options:
  --verbose [VERBOSE], -v [VERBOSE]
                        Print more verbose messages for each additional
                        verbose level.
  -L FILE, --log_file FILE
                        Name and path of log file

pipeline arguments:
  -T JOBNAME, --target_tasks JOBNAME
                        Target task(s) of pipeline.
  -j N, --jobs N        Allow N jobs (commands) to run simultaneously.
  --use_threads         Use multiple threads rather than processes. Needs
                        --jobs N with N > 1
  -n, --just_print      Don't actually run any commands; just print the
                        pipeline.
  --touch_files_only    Don't actually run the pipeline; just 'touch' the
                        output for each task to make them appear up to date.
  --recreate_database   Don't actually run the pipeline; just recreate the
                        checksum database.
  --checksum_file_name FILE
                        Path of the checksum file.
  --flowchart FILE      Don't run any commands; just print pipeline as a
                        flowchart.
  --key_legend_in_graph
                        Print out legend and key for dependency graph.
  --draw_graph_horizontally
                        Draw horizontal dependency graph.
  --flowchart_format FORMAT
                        format of dependency graph file. Can be 'pdf', 'svg',
                        'svgz' (Structured Vector Graphics), 'pdf', 'png'
                        'jpg' (bitmap graphics) etc
  --forced_tasks JOBNAME
                        Task(s) which will be included even if they are up to
                        date.

Configuration file

You must supply a configuration file for the pipeline in YAML format.

Here is an example:

# Default settings for the pipeline stages.
# These can be overridden in the stage settings below.

defaults:
    # Number of CPU cores to use for the task
    cores: 1
    # Maximum memory in gigabytes for a cluster job
    mem: 4
    # VLSCI account for quota
    account: VR0002
    queue: main
    # Maximum allowed running time on the cluster in Hours:Minutes
    walltime: '1:00'
    # Load modules for running a command on the cluster.
    modules: 
    # Run on the local machine (where the pipeline is run)
    # instead of on the cluster. False means run on the cluster.
    local: False

# Stage-specific settings. These override the defaults above.
# Each stage must have a unique name. This name will be used in
# the pipeine to find the settings for the stage.

stages:
    # Run quality checks on the FASTQ files using fastQC
    fastqc:
        walltime: '10:00'
        mem: 8
        modules:
            - 'fastqc/0.10.1'

    # Index the hg19 human genome reference with BWA
    index_reference_bwa:
        walltime: '10:00'
        mem: 8
        modules:
            - 'bwa-intel/0.7.12' 
    
    # Index the hg19 human genome reference with samtools
    index_reference_samtools:
        walltime: '10:00'
        mem: 8
        modules:
            - 'samtools-intel/1.1'
    
    # Align paired end FASTQ files to the reference
    align_bwa:
        cores: 8
        walltime: '48:00'
        mem: 32
        modules:
            - 'bwa-intel/0.7.12'
            - 'samtools-intel/1.1'

# The Human Genome in FASTA format

reference: /path/to/reference/genome.fa 

# The input FASTQ files.

fastqs:
   - /path/to/fastqs/sample1_R1.fastq.gz
   - /path/to/fastqs/sample1_R2.fastq.gz
   - /path/to/fastqs/sample2_R1.fastq.gz
   - /path/to/fastqs/sample2_R2.fastq.gz

read_groups:
   'sample1': '@RG\tID:id1\tPU:pu1\tSM:sample1\tPL:ILLUMINA\tLB:lib_sample1'
   'sample2': '@RG\tID:id2\tPU:pu2\tSM:sample2\tPL:ILLUMINA\tLB:lib_sample2'

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