bio-workflow-management-wdl-workflows
Create portable bioinformatics pipelines with Workflow Description Language (WDL) using Cromwell or miniwdl execution engines. Use when running GATK best practices pipelines, working with Terra/AnVIL platforms, or building workflows for cloud execution on Google Cloud or AWS.
What this skill does
## Version Compatibility
Reference examples tested with: BWA 0.7.17+, FastQC 0.12+, GATK 4.5+, Nextflow 23.10+, Salmon 1.10+, Snakemake 8.0+, fastp 0.23+, samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
- CLI: `<tool> --version` then `<tool> --help` to confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.
# WDL Workflows
**"Build a WDL pipeline for Terra/AnVIL execution"** -> Define tasks and workflows in WDL (Workflow Description Language) for execution on Cromwell, miniwdl, or cloud platforms (Terra, AnVIL) with built-in GATK best practices support.
- CLI: `cromwell run workflow.wdl` or `miniwdl run workflow.wdl` for execution
- WDL: version 1.0 task/workflow syntax with scatter-gather parallelism
## Basic Task Definition
```wdl
version 1.0
task fastqc {
input {
File fastq
Int threads = 2
}
command <<<
fastqc -t ~{threads} ~{fastq}
>>>
output {
File html = glob("*_fastqc.html")[0]
File zip = glob("*_fastqc.zip")[0]
}
runtime {
docker: "biocontainers/fastqc:v0.11.9"
cpu: threads
memory: "4 GB"
}
}
```
## Simple Workflow
```wdl
version 1.0
workflow rnaseq {
input {
File fastq_1
File fastq_2
File salmon_index
}
call fastp {
input:
reads_1 = fastq_1,
reads_2 = fastq_2
}
call salmon_quant {
input:
reads_1 = fastp.trimmed_1,
reads_2 = fastp.trimmed_2,
index = salmon_index
}
output {
File quant_sf = salmon_quant.quant_file
}
}
```
## Task with All Sections
```wdl
version 1.0
task bwa_mem {
input {
File reference
File reference_index
File reads_1
File reads_2
String sample_id
Int threads = 8
}
Int disk_size = ceil(size(reference, "GB") + size(reads_1, "GB") * 3) + 20
command <<<
bwa mem -t ~{threads} -R "@RG\tID:~{sample_id}\tSM:~{sample_id}" \
~{reference} ~{reads_1} ~{reads_2} | \
samtools sort -@ ~{threads} -o ~{sample_id}.sorted.bam
samtools index ~{sample_id}.sorted.bam
>>>
output {
File bam = "~{sample_id}.sorted.bam"
File bai = "~{sample_id}.sorted.bam.bai"
}
runtime {
docker: "biocontainers/bwa:v0.7.17"
cpu: threads
memory: "16 GB"
disks: "local-disk " + disk_size + " HDD"
}
}
```
## Scatter (Parallel Execution)
```wdl
version 1.0
workflow process_samples {
input {
Array[File] fastq_files
File reference
}
scatter (fastq in fastq_files) {
call align {
input:
fastq = fastq,
reference = reference
}
}
output {
Array[File] bam_files = align.bam
}
}
```
## Scatter with Paired Files
```wdl
version 1.0
struct SampleFastqs {
String sample_id
File fastq_1
File fastq_2
}
workflow paired_alignment {
input {
Array[SampleFastqs] samples
File reference
}
scatter (sample in samples) {
call align {
input:
sample_id = sample.sample_id,
reads_1 = sample.fastq_1,
reads_2 = sample.fastq_2,
reference = reference
}
}
output {
Array[File] bams = align.bam
}
}
```
## Conditional Execution
```wdl
version 1.0
workflow conditional_qc {
input {
File fastq
Boolean run_qc = true
}
if (run_qc) {
call fastqc {
input:
fastq = fastq
}
}
output {
File? qc_report = fastqc.html
}
}
```
## Structs and Complex Types
```wdl
version 1.0
struct ReferenceData {
File fasta
File fasta_index
File dict
File? known_sites
}
workflow variant_calling {
input {
ReferenceData reference
Array[File] bam_files
}
scatter (bam in bam_files) {
call haplotype_caller {
input:
bam = bam,
ref_fasta = reference.fasta,
ref_index = reference.fasta_index,
ref_dict = reference.dict
}
}
}
```
## Input JSON
```json
{
"rnaseq.fastq_1": "data/sample1_R1.fq.gz",
"rnaseq.fastq_2": "data/sample1_R2.fq.gz",
"rnaseq.salmon_index": "ref/salmon_index",
"rnaseq.threads": 8
}
```
## Array Inputs JSON
```json
{
"process_samples.samples": [
{
"sample_id": "sample1",
"fastq_1": "data/sample1_R1.fq.gz",
"fastq_2": "data/sample1_R2.fq.gz"
},
{
"sample_id": "sample2",
"fastq_1": "data/sample2_R1.fq.gz",
"fastq_2": "data/sample2_R2.fq.gz"
}
],
"process_samples.reference": "ref/genome.fa"
}
```
## Subworkflows
```wdl
version 1.0
import "qc.wdl" as qc
import "align.wdl" as align
workflow main_pipeline {
input {
File fastq_1
File fastq_2
File reference
}
call qc.quality_control {
input:
reads_1 = fastq_1,
reads_2 = fastq_2
}
call align.alignment {
input:
reads_1 = quality_control.trimmed_1,
reads_2 = quality_control.trimmed_2,
reference = reference
}
}
```
## Runtime Options
```wdl
runtime {
docker: "ubuntu:20.04"
cpu: 4
memory: "8 GB"
disks: "local-disk 100 HDD"
preemptible: 3
maxRetries: 2
zones: "us-central1-a us-central1-b"
bootDiskSizeGb: 15
}
```
## String Interpolation and Expressions
```wdl
version 1.0
task process {
input {
String sample_id
Int memory_gb = 8
Array[File] input_files
}
Int memory_mb = memory_gb * 1000
String output_name = sample_id + ".processed.bam"
command <<<
# Access array elements
process_tool \
--memory ~{memory_mb} \
--inputs ~{sep=' ' input_files} \
--output ~{output_name}
>>>
output {
File result = output_name
}
}
```
## File Size and Disk Calculation
```wdl
version 1.0
task align {
input {
File reads_1
File reads_2
File reference
}
# Calculate disk: input files + 3x for outputs + buffer
Int disk_gb = ceil(size(reads_1, "GB") + size(reads_2, "GB") +
size(reference, "GB") * 2) + 50
command <<<
bwa mem ~{reference} ~{reads_1} ~{reads_2} > aligned.sam
>>>
runtime {
disks: "local-disk " + disk_gb + " SSD"
}
}
```
## Complete RNA-seq Workflow
```wdl
version 1.0
workflow rnaseq_pipeline {
input {
Array[String] sample_ids
Array[File] fastq_1_files
Array[File] fastq_2_files
File salmon_index
Int threads = 8
}
scatter (idx in range(length(sample_ids))) {
call fastp {
input:
sample_id = sample_ids[idx],
reads_1 = fastq_1_files[idx],
reads_2 = fastq_2_files[idx],
threads = threads
}
call salmon_quant {
input:
sample_id = sample_ids[idx],
reads_1 = fastp.trimmed_1,
reads_2 = fastp.trimmed_2,
index = salmon_index,
threads = threads
}
}
output {
Array[File] quant_files = salmon_quant.quant_sf
Array[File] fastp_reports = fastp.json_report
}
}
task fastp {
input {
String sample_id
File reads_1
File reads_2
Int threads = 4
}
command <<<
fastp -i ~{reads_1} -I ~{reads_2} \
-o ~{sample_id}_trimmed_R1.fq.gz \
-O ~{sample_id}_trimmed_R2.fq.gz \
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