Writing a CWL workflow

The Common Workflow Language is a multi-vendor open standard for describing analysis tools and workflows that are portable across a variety of platforms. CWL is the recommended way to develop and run workflows for Arvados. Arvados supports the CWL v1.0 specification.

Note:

This tutorial assumes that you are logged into an Arvados VM instance (instructions for Webshell or Unix or Windows) or you have installed the Arvados Command line SDK and Python SDK on your workstation and have a working environment.

Developing workflows

For an introduction and and detailed documentation about writing CWL, see the CWL User Guide and the CWL Specification .

See Best Practices for writing CWL and Arvados CWL Extensions for additional information about using CWL on Arvados.

Registering a workflow to use in Workbench

Use --create-workflow to register a CWL workflow with Arvados. This enables you to share workflows with other Arvados users, and run them by clicking the Run a process… button on the Workbench Dashboard and on the command line by UUID.

~/arvados/doc/user/cwl/bwa-mem$ arvados-cwl-runner --create-workflow bwa-mem.cwl
arvados-cwl-runner 1.0.20160628195002, arvados-python-client 0.1.20160616015107, cwltool 1.0.20160629140624
2016-07-01 12:21:01 arvados.arv-run[15796] INFO: Upload local files: "bwa-mem.cwl"
2016-07-01 12:21:01 arvados.arv-run[15796] INFO: Uploaded to qr1hi-4zz18-7e0hedrmkuyoei3
2016-07-01 12:21:01 arvados.cwl-runner[15796] INFO: Created template qr1hi-p5p6p-rjleou1dwr167v5
qr1hi-p5p6p-rjleou1dwr167v5

You can provide a partial input file to set default values for the workflow input parameters. You can also use the --name option to set the name of the workflow:

~/arvados/doc/user/cwl/bwa-mem$ arvados-cwl-runner --name "My workflow with defaults" --create-workflow bwa-mem.cwl bwa-mem-template.yml
arvados-cwl-runner 1.0.20160628195002, arvados-python-client 0.1.20160616015107, cwltool 1.0.20160629140624
2016-07-01 14:09:50 arvados.arv-run[3730] INFO: Upload local files: "bwa-mem.cwl"
2016-07-01 14:09:50 arvados.arv-run[3730] INFO: Uploaded to qr1hi-4zz18-0f91qkovk4ml18o
2016-07-01 14:09:50 arvados.cwl-runner[3730] INFO: Created template qr1hi-p5p6p-0deqe6nuuyqns2i
qr1hi-p5p6p-zuniv58hn8d0qd8

Running registered workflows at the command line

You can run a registered workflow at the command line by its UUID:

~/arvados/doc/user/cwl/bwa-mem$ arvados-cwl-runner qr1hi-p5p6p-zuniv58hn8d0qd8 --help
/home/peter/work/scripts/venv/bin/arvados-cwl-runner 0d62edcb9d25bf4dcdb20d8872ea7b438e12fc59 1.0.20161209192028, arvados-python-client 0.1.20161212125425, cwltool 1.0.20161207161158
Resolved 'qr1hi-p5p6p-zuniv58hn8d0qd8' to 'keep:655c6cd07550151b210961ed1d3852cf+57/bwa-mem.cwl'
usage: qr1hi-p5p6p-zuniv58hn8d0qd8 [-h] [--PL PL] --group_id GROUP_ID
                                   --read_p1 READ_P1 [--read_p2 READ_P2]
                                   [--reference REFERENCE] --sample_id
                                   SAMPLE_ID
                                   [job_order]

positional arguments:
  job_order             Job input json file

optional arguments:
  -h, --help            show this help message and exit
  --PL PL
  --group_id GROUP_ID
  --read_p1 READ_P1     The reads, in fastq format.
  --read_p2 READ_P2     For mate paired reads, the second file (optional).
  --reference REFERENCE
                        The index files produced by `bwa index`
  --sample_id SAMPLE_ID

Using cwltool

When developing a workflow, it is often helpful to run it on the local host to avoid the overhead of submitting to the cluster. To execute a workflow only on the local host (without submitting jobs to an Arvados cluster) you can use the cwltool command. Note that when using cwltool you must have the input data accessible on the local file system using either arv-mount or arv-get to fetch the data from Keep.

~/arvados/doc/user/cwl/bwa-mem$ arv-get 2463fa9efeb75e099685528b3b9071e0+438/ .
156 MiB / 156 MiB 100.0%
~/arvados/doc/user/cwl/bwa-mem$ arv-get ae480c5099b81e17267b7445e35b4bc7+180/ .
23 MiB / 23 MiB 100.0%
~/arvados/doc/user/cwl/bwa-mem$ cwltool bwa-mem-input.yml bwa-mem-input-local.yml
cwltool 1.0.20160629140624
[job bwa-mem.cwl] /home/example/arvados/doc/user/cwl/bwa-mem$ docker \
    run \
    -i \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/19.fasta.ann:/var/lib/cwl/job979368791_bwa-mem/19.fasta.ann:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/HWI-ST1027_129_D0THKACXX.1_1.fastq:/var/lib/cwl/job979368791_bwa-mem/HWI-ST1027_129_D0THKACXX.1_1.fastq:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/19.fasta.sa:/var/lib/cwl/job979368791_bwa-mem/19.fasta.sa:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/19.fasta.amb:/var/lib/cwl/job979368791_bwa-mem/19.fasta.amb:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/19.fasta.pac:/var/lib/cwl/job979368791_bwa-mem/19.fasta.pac:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/HWI-ST1027_129_D0THKACXX.1_2.fastq:/var/lib/cwl/job979368791_bwa-mem/HWI-ST1027_129_D0THKACXX.1_2.fastq:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem/19.fasta.bwt:/var/lib/cwl/job979368791_bwa-mem/19.fasta.bwt:ro \
    --volume=/home/example/arvados/doc/user/cwl/bwa-mem:/var/spool/cwl:rw \
    --volume=/tmp/tmpgzyou9:/tmp:rw \
    --workdir=/var/spool/cwl \
    --read-only=true \
    --log-driver=none \
    --user=1001 \
    --rm \
    --env=TMPDIR=/tmp \
    --env=HOME=/var/spool/cwl \
    biodckr/bwa \
    bwa \
    mem \
    -t \
    1 \
    -R \
    '@RG	ID:arvados_tutorial	PL:illumina	SM:HWI-ST1027_129' \
    /var/lib/cwl/job979368791_bwa-mem/19.fasta \
    /var/lib/cwl/job979368791_bwa-mem/HWI-ST1027_129_D0THKACXX.1_1.fastq \
    /var/lib/cwl/job979368791_bwa-mem/HWI-ST1027_129_D0THKACXX.1_2.fastq > /home/example/arvados/doc/user/cwl/bwa-mem/HWI-ST1027_129_D0THKACXX.1_1.sam
[M::bwa_idx_load_from_disk] read 0 ALT contigs
[M::process] read 100000 sequences (10000000 bp)...
[M::mem_pestat] # candidate unique pairs for (FF, FR, RF, RR): (0, 4745, 1, 0)
[M::mem_pestat] skip orientation FF as there are not enough pairs
[M::mem_pestat] analyzing insert size distribution for orientation FR...
[M::mem_pestat] (25, 50, 75) percentile: (154, 181, 214)
[M::mem_pestat] low and high boundaries for computing mean and std.dev: (34, 334)
[M::mem_pestat] mean and std.dev: (185.63, 44.88)
[M::mem_pestat] low and high boundaries for proper pairs: (1, 394)
[M::mem_pestat] skip orientation RF as there are not enough pairs
[M::mem_pestat] skip orientation RR as there are not enough pairs
[M::mem_process_seqs] Processed 100000 reads in 9.848 CPU sec, 9.864 real sec
[main] Version: 0.7.12-r1039
[main] CMD: bwa mem -t 1 -R @RG	ID:arvados_tutorial	PL:illumina	SM:HWI-ST1027_129 /var/lib/cwl/job979368791_bwa-mem/19.fasta /var/lib/cwl/job979368791_bwa-mem/HWI-ST1027_129_D0THKACXX.1_1.fastq /var/lib/cwl/job979368791_bwa-mem/HWI-ST1027_129_D0THKACXX.1_2.fastq
[main] Real time: 10.061 sec; CPU: 10.032 sec
Final process status is success
{
    "aligned_sam": {
        "size": 30738959,
        "path": "/home/example/arvados/doc/user/cwl/bwa-mem/HWI-ST1027_129_D0THKACXX.1_1.sam",
        "checksum": "sha1$0c668cca45fef02397bb5302880526d300ee4dac",
        "class": "File"
    }
}

If you get the error JavascriptException: Long-running script killed after 20 seconds. this may be due to the Dockerized Node.js engine taking too long to start. You may address this by installing Node.js locally (run apt-get install nodejs on Debian or Ubuntu) or by specifying a longer timeout with the --eval-timeout option. For example, run the workflow with cwltool --eval-timeout=40 for a 40-second timeout.

Making workflows directly executable

You can make a workflow file directly executable (cwl-runner should be an alias to arvados-cwl-runner) by adding the following line to the top of the file:

#!/usr/bin/env cwl-runner
~/arvados/doc/user/cwl/bwa-mem$ ./bwa-mem.cwl bwa-mem-input.yml
arvados-cwl-runner 1.0.20160628195002, arvados-python-client 0.1.20160616015107, cwltool 1.0.20160629140624
2016-06-30 14:56:36 arvados.arv-run[27002] INFO: Upload local files: "bwa-mem.cwl"
2016-06-30 14:56:36 arvados.arv-run[27002] INFO: Uploaded to qr1hi-4zz18-h7ljh5u76760ww2
2016-06-30 14:56:40 arvados.cwl-runner[27002] INFO: Submitted job qr1hi-8i9sb-fm2n3b1w0l6bskg
2016-06-30 14:56:41 arvados.cwl-runner[27002] INFO: Job bwa-mem.cwl (qr1hi-8i9sb-fm2n3b1w0l6bskg) is Running
2016-06-30 14:57:12 arvados.cwl-runner[27002] INFO: Job bwa-mem.cwl (qr1hi-8i9sb-fm2n3b1w0l6bskg) is Complete
2016-06-30 14:57:12 arvados.cwl-runner[27002] INFO: Overall process status is success
{
    "aligned_sam": {
        "path": "keep:54325254b226664960de07b3b9482349+154/HWI-ST1027_129_D0THKACXX.1_1.sam",
        "checksum": "sha1$0dc46a3126d0b5d4ce213b5f0e86e2d05a54755a",
        "class": "File",
        "size": 30738986
    }
}

You can even make an input file directly executable the same way with the following two lines at the top:

#!/usr/bin/env cwl-runner
cwl:tool: bwa-mem.cwl
~/arvados/doc/user/cwl/bwa-mem$ ./bwa-mem-input.yml
arvados-cwl-runner 1.0.20160628195002, arvados-python-client 0.1.20160616015107, cwltool 1.0.20160629140624
2016-06-30 14:56:36 arvados.arv-run[27002] INFO: Upload local files: "bwa-mem.cwl"
2016-06-30 14:56:36 arvados.arv-run[27002] INFO: Uploaded to qr1hi-4zz18-h7ljh5u76760ww2
2016-06-30 14:56:40 arvados.cwl-runner[27002] INFO: Submitted job qr1hi-8i9sb-fm2n3b1w0l6bskg
2016-06-30 14:56:41 arvados.cwl-runner[27002] INFO: Job bwa-mem.cwl (qr1hi-8i9sb-fm2n3b1w0l6bskg) is Running
2016-06-30 14:57:12 arvados.cwl-runner[27002] INFO: Job bwa-mem.cwl (qr1hi-8i9sb-fm2n3b1w0l6bskg) is Complete
2016-06-30 14:57:12 arvados.cwl-runner[27002] INFO: Overall process status is success
{
    "aligned_sam": {
        "path": "keep:54325254b226664960de07b3b9482349+154/HWI-ST1027_129_D0THKACXX.1_1.sam",
        "checksum": "sha1$0dc46a3126d0b5d4ce213b5f0e86e2d05a54755a",
        "class": "File",
        "size": 30738986
    }
}

Previous: Introduction to Crunch Next: Best Practices for writing CWL

The content of this documentation is licensed under the Creative Commons Attribution-Share Alike 3.0 United States licence.
Code samples in this documentation are licensed under the Apache License, Version 2.0.