Description

This workflow represents the GATK Best Practices for SNP and INDEL calling on DNA data.

Starting from a processed BAM file, the workflow performs variant calling with respect to the reference genome. Depending on HaplotypeCaller's output file type (VCF or g.VCF, the resulting file of this workflow can be used as a stand alone result for single-sample analysis, or as one of the cohort files downstream joint calling analysis. On the GATK website you can find more detailed information about calling germline variants for single sample or joint calling analysis [1].

Common Use Cases

• The haplotypecaller-gvcf-gatk4 (original WDL name) workflow [1] runs the HaplotypeCaller tool from GATK4 in GVCF mode on a single sample according to GATK Best Practices.

• To run HaplotypeCaller in a mode appropriate for joint calling analysis, one needs to set (--emit_ref_confidence) parameter to GVCF.

• When executed, the workflow scatters the HaplotypeCaller tool over the Calling intervals file (--in_intervals).

• The resulting g.VCF files are merged with GATK MergeVCF.

• The output file produced will be a single g.VCF file which can be further processed in joint-discovery workflow.

• By default, the output file is compressed with gzip, leading to a G.VCF.GZ extension.

• This workflow can also be used for single sample analysis. For that purpose, it produces a VCF file which is obtained by setting (the --emit_ref_confidence) parameter to NONE.

Changes Introduced by Seven Bridges

• The original Generic germline variant per-sample calling WDL implementation has a step called CramToBamTask which accepts CRAM files and converts them to BAM files with samtools view, while also indexing them. In this CWL implementation, this step is skipped as GATK HaplotypeCaller has the option to work with CRAM files. Keep in mind that CRAM files need to be indexed.

• To enable scattering of GATK Haplotypecallier tool, we have introduced the GATK IntervalListTool, solution given in GATK Production Germline short variant per-sample calling [2].

Common Issues and Important Notes

• The HaplotypeCaller app uses Intervals list to restrict processing to specific genomic intervals. You can set the Scatter count value in order to split Intervals list into smaller intervals. HaplotypeCaller processes these intervals in parallel, which can significantly reduce workflow execution time in some cases.

• The workflow accepts multiple flowcell BAMs on input, however, they must all share the same sample ID. Otherwise, some GATK tools will fail.

• Running a batch task: Batching is performed by Sample ID metadata field on the Aligned and Processed BAM input port. For running analyses in batches, it is necessary to set Sample ID metadata for each Processed and aligned BAM file.

Performance Benchmarking

BAM Input size	Experiment type	Coverage	Duration	Cost	Instance
55.8GiB	WGS (scatter count = 20)	~50x	17h 35min	$9.42	c4.2xlarge
55.8GiB	WGS (scatter count = 80)	~50x	10h 32min	$5.64	c4.2xlarge
24.6GiB	WGS (scatter count = 80)	~10x	4h 12min	$2.25	c4.2xlarge
3.5GiB	WES (scatter count = 1)	~70x	17min	$0.16	c4.2xlarge
1.9GiB	WES (scatter count = 1)	~40x	11min	$0.11	c4.2xlarge
1.1GiB	WES (scatter count = 1)	~20x	9min	$0.08	c4.2xlarge
434MiB	WES (scatter count = 1)	~10x	6min	$0.06	c4.2xlarge

API Python Implementation

The app's draft task can also be submitted via the API. In order to learn how to get your Authentication token and API endpoint for corresponding platform visit our documentation.

# Initialize the SBG Python API
from sevenbridges import Api
api = Api(token="enter_your_token", url="enter_api_endpoint")
project_id = "your_username/project"
app_id = "your_username/project/app"
# Replace inputs with appropriate values
inputs = {
        "in_reference": api.files.query(project=project_id, names=["Homo_sapiens_assembly38.fasta"])[0], 
	"in_alignments": list(api.files.query(project=project_id, names=["HCC1143BL_WES_1.processed.bam"])), 
	"in_intervals": list(api.files.query(project=project_id, names=["wgs_calling_regions.hg38.interval_list"]))}

# Creates draft task
task = api.tasks.create(name="GATK Best Practice Germline snps and indels 4.1.0.0 - API Run", project=project_id, app=app_id, inputs=inputs, run=False)

Instructions for installing and configuring the API Python client, are provided on github. For more information about using the API Python client, consult the client documentation. More examples are available here.

Additionally, API R and API Java clients are available. To learn more about using these API clients please refer to the API R client documentation, and API Java client documentation.

References.

[1] Broad germline SNPS and INDELS

[2] Broad Producion WGS germline SNPs and INDELs# Broad-Best-Practice-Germline-snps-and-indels-variant-calling-CWL1.0-workflow-GATK-4.1.0.0