Build a recalibration model to score variant quality for filtering purposes. It is highly recommended to follow GATK best practices when using this module, the gaussian mixture model requires a large number of samples to be used for the tool to produce optimal results. For example, 30 samples for exome data. For more details see


Name (Type)

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’ ]

vcf (file)

input vcf file containing the variants to be recalibrated


tbi (file)

tbi file matching with -vcf


resource_vcf (file)

all resource vcf files that are used with the corresponding ‘—resource’ label


resource_tbi (file)

all resource tbi files that are used with the corresponding ‘—resource’ label


labels (string)

necessary arguments for GATK VariantRecalibrator. Specified to directly match the resources provided. More information can be found at

fasta (file)

The reference fasta file


fai (file)

Index of reference fasta file


dict (file)

GATK sequence dictionary



Name (Type)

recal (file)

Output recal file used by ApplyVQSR


idx (file)

Index file for the recal output file


tranches (file)

Output tranches file used by ApplyVQSR


plots (file)

Optional output rscript file to aid in visualization of the input data and learned model.


version (file)

File containing software versions




Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size.