Stian Soiland-Reyes

eScience lab, The University of Manchester

@soilandreyes

https://orcid.org/0000-0001-9842-9718

https://slides.com/soilandreyes/2018-12-11-cwl/

 

BioExcel/MolSSI Workshop on
Workflows in Biomolecular Simulations
2018-12-11, Barcelona

This work has been done as part of the BioExcel CoE (www.bioexcel.eu), a project funded by the European Union contract H2020-EINFRA-2015-1-675728.

Introduction to
Common Workflow Language

Findable

Accessible

Interoperable

Reusable

To be Findable:

F1. (meta)data are assigned a globally unique and persistent identifier

F2. data are described with rich metadata (defined by R1 below)

F3. metadata clearly and explicitly include the identifier of the data it describes

F4. (meta)data are registered or indexed in a searchable resource

To be Accessible:

A1. (meta)data are retrievable by their identifier using a standardized communications protocol

A1.1 the protocol is open, free, and universally implementable

A1.2 the protocol allows for an authentication and authorization procedure, where necessary

A2. metadata are accessible, even when the data are no longer available

To be Interoperable:

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.

I2. (meta)data use vocabularies that follow FAIR principles

I3. (meta)data include qualified references to other (meta)data

To be Reusable:

R1. meta(data) are richly described with a plurality of accurate and relevant attributes

R1.1. (meta)data are released with a clear and accessible data usage license

R1.2. (meta)data are associated with detailed provenance

R1.3. (meta)data meet domain-relevant community standards

cwlVersion: v1.0
class: Workflow
inputs:
  inp: File
  ex: string

outputs:
  classout:
    type: File
    outputSource: compile/classfile

steps:
  untar:
    run: tar-param.cwl
    in:
      tarfile: inp
      extractfile: ex
    out: [example_out]

  compile:
    run: arguments.cwl
    in:
      src: untar/example_out
    out: [classfile]

Building CWL workflows

cwlVersion: v1.0
class: Workflow

inputs:
  toConvert: File


outputs:
  converted: 
    type: File
    outputSource: convertMethylation/converted
  combined: 
    type: File
    outputSource: mergeSymmetric/combined


steps:
  convertMethylation:
    run: interconverter.cwl
    in:
      toConvert: toConvert
    out: [converted]
  mergeSymmetric:
    run: symmetriccpgs.cwl
    in:
      toCombine: convertMethylation/converted
    out: [combined]
cwlVersion: v1.0
class: CommandLineTool
baseCommand: interconverter.sh
hints:
  - class: DockerRequirement
    dockerPull: "quay.io/neksa/screw-tool"
arguments: ["-d", $(runtime.outdir)]
inputs:
  toConvert:
    type: File
    inputBinding:
      prefix: -i
outputs:
  converted:
    type: File
    outputBinding:
      glob: "*.meth"
cwlVersion: v1.0
class: CommandLineTool
baseCommand: symmetriccpgs.sh
arguments: ["-d", $(runtime.outdir)]
hints:
  - class: DockerRequirement
    dockerPull: "quay.io/neksa/screw-tool"

inputs:
  toCombine:
    type: File
    inputBinding:
      prefix: -i
outputs:
  combined:
    type: File
    outputBinding:
      glob: "*.sym"

Over 13000 CWL Descriptions on GitHub
(of which 3,865 workflows)

 

cwlVersion: v1.0
class: Workflow
label: EMG QC workflow, (paired end version). Benchmarking with MG-RAST expt.

requirements:
 - class: SubworkflowFeatureRequirement
 - class: SchemaDefRequirement
   types: 
    - $import: ../tools/FragGeneScan-model.yaml
    - $import: ../tools/trimmomatic-sliding_window.yaml
    - $import: ../tools/trimmomatic-end_mode.yaml
    - $import: ../tools/trimmomatic-phred.yaml

inputs:
  reads:
    type: File
    format: edam:format_1930  # FASTQ

outputs:
  processed_sequences:
    type: File
    outputSource: clean_fasta_headers/sequences_with_cleaned_headers

steps:
  trim_quality_control:
    doc: |
      Low quality trimming (low quality ends and sequences with < quality scores
      less than 15 over a 4 nucleotide wide window are removed)
    run: ../tools/trimmomatic.cwl
    in:
      reads1: reads
      phred: { default: '33' }
      leading: { default: 3 }
      trailing: { default: 3 }
      end_mode: { default: SE }
      minlen: { default: 100 }
      slidingwindow:
        default:
          windowSize: 4
          requiredQuality: 15
    out: [reads1_trimmed]

  convert_trimmed-reads_to_fasta:
    run: ../tools/fastq_to_fasta.cwl
    in:
      fastq: trim_quality_control/reads1_trimmed
    out: [ fasta ]

  clean_fasta_headers:
    run: ../tools/clean_fasta_headers.cwl
    in:
      sequences: convert_trimmed-reads_to_fasta/fasta
    out: [ sequences_with_cleaned_headers ]


$namespaces:
 edam: http://edamontology.org/
 s: http://schema.org/
$schemas:
 - http://edamontology.org/EDAM_1.16.owl
 - https://schema.org/docs/schema_org_rdfa.html

s:license: "https://www.apache.org/licenses/LICENSE-2.0"
s:copyrightHolder: "EMBL - European Bioinformatics Institute"

CWL Features

Interoperability

.. and portability

cwltool: Local (Linux, OS X, Windows)

Arvados: AWS, GCP, Azure, Slurm

Toil: AWS, Azure, GCP, Grid Engine, LSF, Mesos, OpenStack, Slurm, PBS/Torque

Rabix Bunny: Local(Linux, OS X), GA4GH TES

cwl-tes: Local, GCP, AWS, HTCondor, Grid Engine, PBS/Torque, Slurm

CWL-Airflow: Linux, OS X

REANA: Kubernetes, CERN OpenStack

cromwell: local, HPC, Google, HtCondor

CWLEXEC: IBM Spectrum LSF

XENON: any Xenon backend: local, ssh, SLURM, Torque, Grid Engine

Which CWL engine runs where?

#!/usr/bin/env cwl-runner

cwlVersion: v1.0

class: CommandLineTool

baseCommand: ["gmx", "pdb2gmx"]

arguments: ["-o", "processed.gro"]

inputs:
  pdb:
    type: string
    inputBinding:
      prefix: -f
  water:
    type: File
    inputBinding:
      prefix: -water
    default: spce

outputs:
  processed_gro:
    type: File
    outputBinding:
      glob: processed.gro

Portable command line tools

Where to find command line tools?

cwlVersion: v1.0
class: CommandLineTool
baseCommand: node
hints:
  DockerRequirement:
    dockerPull: gromacs/gromacs:2018.4

Let's add some identifiers!

hints:
  SoftwareRequirement:
    packages:
    - package: gromacs
      version:
      - '2018.4'
      specs:
      - https://packages.debian.org/gromacs
      - https://anaconda.org/bioconda/gromacs
      - https://bio.tools/gromacs
      - https://identifiers.org/rrid/RRID:SCR_014565
      - https://hpc.example.edu/modules/gromacs/2018.4
  DockerRequirement:
    dockerPull: gromacs/gromacs:2018.4

class: CommandLineTool
hints:
  SoftwareRequirement:
    packages:
      gromacs:
        version: [ "2018.4" ]

baseCommand: ["gmx", "pdb2gmx"]
#..

Automatic tool installation

module load gromacs/2018.4
apt-get install gromacs=2018.4*
conda install gromacs=2018.4
<dependency_resolvers>
  <modules modulecmd="/opt/bin/modulecmd" />
  <tool_shed_packages />
  <galaxy_packages />
  <conda />

  <modules modulecmd="/opt/bin/modulecmd" versionless="true" />
  <galaxy_packages versionless="true" />
  <conda versionless="true" />
</dependency_resolvers>

Package resolution

tool_dependency_dir/
  gromacs/
    2018.4/
      bin/
      env.sh

Dependency resolution by CWLTool and Toil

#!/usr/bin/env cwl-runner

cwlVersion: v1.0
class: CommandLineTool
baseCommand: echo

requirements:
  InlineJavascriptRequirement: {}

inputs: []
outputs:
  example_out:
    type: stdout
stdout: output.txt
arguments:
  - prefix: -A
    valueFrom: $(1+1)
  - prefix: -B
    valueFrom: $("/foo/bar/baz".split('/').slice(-1)[0])
  - prefix: -C
    valueFrom: |
      ${
        var r = [];
        for (var i = 10; i >= 1; i--) {
          r.push(i);
        }
        return r;
      }

JavaScript expressions

arguments: ['--cpus', $(runtime.cores)]

requirements:
  - class: ResourceRequirement
    ramMin: 42000
    coresMin: 1
    tmpdirMin: 40000
- class: InlineJavascriptRequirement

Not just files

Secondary files

Inline files

Directories

Arrays of files

Enums

JSON records (string, int, array, dict)

 

Workflow Engine is free on how to handle data management, e.g. data store or file copying

Dataflow features

Optional inputs (tool reuse)

Sub-workflows (reuse workflow as a tool)

Task Parallelization (step execute when data is ready)

Scattering (multiple tasks from single array)

Merge (multiple inputs to single array)

Work in progress

 

towards CWL 2.x

 

Conditional branching (switch statement)

Looping

Provenance

Who ran it?

When did it run?

Where did it run?

What workflow ran?

Which tool versions?

What data was created?

Khan et al,
Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv
Submitted to GigaScience
https://doi.org/10.5281/zenodo.1966881

$ cwlprov --help
usage: cwlprov [-h] [--version] [--directory DIRECTORY] [--relative]
            [--absolute] [--output OUTPUT] [--verbose] [--quiet] [--hints]
            [--no-hints]
            {validate,info,who,prov,inputs,outputs,run,runs,rerun,derived,runtimes}
            ...

cwlprov explores Research Objects containing provenance of Common Workflow
Language executions. <https://w3id.org/cwl/prov/>

commands:
{validate,info,who,prov,inputs,outputs,run,runs,rerun,derived,runtimes}
    validate            Validate the CWLProv Research Object
    info                show research object Metadata
    who                 show Who ran the workflow
    prov                export workflow execution Provenance in PROV format
    inputs              list workflow/step Input files/values
    outputs             list workflow/step Output files/values
    run                 show workflow Execution log
    runs                List all workflow executions in RO
    rerun               Rerun a workflow or step
    derived             list what was Derived from a data item, based on
                        activity usage/generation
    runtimes            calculate average step execution Runtimes

(venv3) stain@biggie:~/src/cwlprov-py/test/nested-cwlprov-0.3.0$ cwlprov run
2018-08-08 22:44:06.573330 Flow 39408a40-c1c8-4852-9747-87249425be1e [ Run of workflow/packed.cwl#main 
2018-08-08 22:44:06.691722 Step 4f082fb6-3e4d-4a21-82e3-c685ce3deb58   Run of workflow/packed.cwl#main/create-tar  (0:00:00.010133)
2018-08-08 22:44:06.702976 Step 0cceeaf6-4109-4f08-940b-f06ac959944a * Run of workflow/packed.cwl#main/compile  (unknown duration)
2018-08-08 22:44:12.680097 Flow 39408a40-c1c8-4852-9747-87249425be1e ] Run of workflow/packed.cwl#main  (0:00:06.106767)
Legend:
[ Workflow start
* Nested provenance, use UUID to explore: cwlprov run 0cceeaf6-4109-4f08-940b-f06ac959944a
] Workflow end

(venv3) stain@biggie:~/src/cwlprov-py/test/nested-cwlprov-0.3.0$ cwlprov run 0cceeaf6-4109-4f08-940b-f06ac959944a
2018-08-08 22:44:06.607210 Flow 0cceeaf6-4109-4f08-940b-f06ac959944a [ Run of workflow/packed.cwl#main 
2018-08-08 22:44:06.707070 Step 83752ab4-8227-4d4a-8baa-78376df34aed   Run of workflow/packed.cwl#main/untar  (0:00:00.008149)
2018-08-08 22:44:06.718554 Step f56d8478-a190-4251-84d9-7f69fe0f6f8b   Run of workflow/packed.cwl#main/argument  (0:00:00.532052)
2018-08-08 22:44:07.251588 Flow 0cceeaf6-4109-4f08-940b-f06ac959944a ] Run of workflow/packed.cwl#main  (0:00:00.644378)
Legend:
[ Workflow start
] Workflow end
stain@biggie:~/src/cwlprov-py/test/nested-cwlprov-0.3.0$ cwlprov outputs 4f082fb6-3e4d-4a21-82e3-c685ce3deb58 --format=files
Output tar:
data/c0/c0fd5812fe6d8d91fef7f4f1ba3a462500fce0c5

stain@biggie:~/src/cwlprov-py/test/nested-cwlprov-0.3.0$ tar tfv `cwlprov -q outputs 4f082fb6-3e4d-4a21-82e3-c685ce3deb58 --format=files`
-rw-r--r-- stain/stain     115 2018-08-08 23:44 Hello.java

Inspecting step runs

2018-12-11 Common Workflow Language

By Stian Soiland-Reyes

2018-12-11 Common Workflow Language

  • 623
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