Mutect2 **BETA**

Call somatic SNVs and indels via local assembly of haplotypes

Category VCF Tools


Overview

Call somatic short variants, both SNVs and indels, via local assembly of haplotypes

Mutect2 calls somatic single nucleotide (SNV) and insertion and deletion (indel) variants. The caller combines the DREAM challenge-winning somatic genotyping engine of the original MuTect (Cibulskis et al., 2013) with the assembly-based machinery of HaplotypeCaller. Although we present the tool for somatic analyses, it may also apply to other contexts.

How GATK4 Mutect2 differs from GATK3 MuTect2

(i) The filtering functionality is now a separate tool called FilterMutectCalls. To filter further based on sequence context artifacts, additionally use FilterByOrientationBias.
(ii) If using a known germline variants resource, then it must contain population allele frequencies, e.g. from gnomAD or the 1000 Genomes Project. The VCF INFO field contains the allele frequency (AF) tag. See below or the GATK Resource Bundle for an example.
(iii) To create the panel of normals (PoN), call on each normal sample using Mutect2's tumor-only mode and then use GATK4's CreateSomaticPanelOfNormals. This contrasts with the GATK3 workflow, which uses an artifact mode in MuTect2 and CombineVariants for PoN creation. In GATK4, omitting filtering with FilterMutectCalls achieves the same artifact mode.
(iv) Instead of using a maximum likelihood estimate, GATK4 Mutect2 marginalizes over allele fractions. GATK3 MuTect2 directly uses allele depths (AD) to estimate allele fractions and calculate likelihoods. In contrast, GATK4 Mutect2 factors for the statistical error inherent in allele depths by marginalizing over allele fractions when calculating likelihoods.
(v) GATK4 Mutect2 recommends including contamination estimates with the -contaminationFile option from CalculateContamination, which in turn relies on the results of GetPileupSummaries.

What remains unchanged is that neither tool versions call on seeming loss of heterozygosity (LoH) events. To detect LoH, see the Copy Number Variant (CNV) and AllelicCNV workflows.

Here is an example of a known variants resource with population allele frequencies:

     #CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO
      1       10067   .       T       TAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCC      30.35   PASS    AC=3;AF=7.384E-5
      1       10108   .       CAACCCT C       46514.32        PASS    AC=6;AF=1.525E-4
      1       10109   .       AACCCTAACCCT    AAACCCT,*       89837.27        PASS    AC=48,5;AF=0.001223,1.273E-4
      1       10114   .       TAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAACCCTAACCCTAACCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAAACCCTA  *,CAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAACCCTAACCCTAACCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAAACCCTA,T      36728.97        PASS    AC=55,9,1;AF=0.001373,2.246E-4,2.496E-5
      1       10119   .       CT      C,*     251.23  PASS    AC=5,1;AF=1.249E-4,2.498E-5
      1       10120   .       TA      CA,*    14928.74        PASS    AC=10,6;AF=2.5E-4,1.5E-4
      1       10128   .       ACCCTAACCCTAACCCTAAC    A,*     285.71  PASS    AC=3,1;AF=7.58E-5,2.527E-5
      1       10131   .       CT      C,*     378.93  PASS    AC=7,5;AF=1.765E-4,1.261E-4
      1       10132   .       TAACCC  *,T     18025.11        PASS    AC=12,2;AF=3.03E-4,5.049E-5
 

How Mutect2 works compared to HaplotypeCaller

Overall, Mutect2 works similarly to HaplotypeCaller, but with a few key differences.

(i) GVCF calling is not a feature of Mutect2. (ii) While HaplotypeCaller relies on a fixed ploidy assumption to inform its genotype likelihoods that are the basis for genotype probabilities (PL), Mutect2 allows for varying ploidy in the form of allele fractions for each variant. Varying allele fractions is often seen within a tumor sample due to fractional purity, multiple subclones and/or copy number variation. (iii) Mutect2 also differs from the HaplotypeCaller in that it can apply various prefilters to sites and variants depending on the use of a matched normal (--normalSampleName), a panel of normals (PoN; --normal_panel) and/or a common population variant resource containing allele-specific frequencies (--germline_resource). If provided, Mutect2 uses the PoN to filter sites and the germline resource and matched normal to filter alleles. (iv) Mutect2's default variant site annotations differ from those of HaplotypeCaller. See the --annotation parameter description for a list. (v) Finally, Mutect2 has additional parameters not available to HaplotypeCaller that factor in the decision to reassemble a genomic region, factor in likelihood calculations that then determine whether to emit a variant, or factor towards filtering. These parameters include the following and are each described further in the arguments section.

--min_variants_in_pileup ==> active region determination
--minNormalVariantFraction ==> active region determination
--tumorStandardDeviationsThreshold ==> active region determination
--af_of_alleles_not_in_resource ==> germline variant prior
--log_somatic_prior ==> somatic variant prior
--normal_lod ==> filter threshold for variants in tumor not being in the normal, i.e. germline-risk filter
--tumor_lod_to_emit ==> cutoff for tumor variants to appear in callset

Further points of interest

Additional parameters that factor towards filtering, including normal_artifact_lod (default threshold 0.0) and tumor_lod (default threshold 5.3), are available in FilterMutectCalls. While the tool calculates normal_lod with a fixed ploidy assumption given by the --sample_ploidy option (default is 2), it calculates normal_artifact_lod with the same approach it uses for tumor_lod, i.e. with a variable ploidy assumption.

If the normal artifact log odds becomes large, then FilterMutectCalls applies the artifact-in-normal filter. For matched normal samples with tumor contamination, consider increasing the normal_artifact_lod threshold.
The tumor log odds, which is calculated independently of any matched normal, determines whether to filter a tumor variant. Variants with tumor LODs exceeding the threshold pass filtering.

If a variant is absent from a given germline resource, then the value for --af_of_alleles_not_in_resource applies. For example, gnomAD's 16,000 samples (~32,000 homologs per locus) becomes a probability of one in 32,000 or less. Thus, an allele's absence from the germline resource becomes evidence that it is not a germline variant.

Examples

Example commands show how to run Mutect2 for typical scenerios.

Tumor with matched normal

Given a matched normal, Mutect2 is designed to call somatic variants only. The tool includes logic to skip emitting variants that are clearly present in the germline based on the evidence present in the matched normal. This is done at an early stage to avoid spending computational resources on germline events. If the variant's germline status is borderline, then Mutect2 will emit the variant to the callset with a germline-risk filter. Such filtered emissions enable manual review.

 gatk-launch --javaOptions "-Xmx4g" Mutect2 \
   -R ref_fasta.fa \
   -I tumor.bam \
   -tumor tumor_sample_name \
   -I normal.bam \
   -normal normal_sample_name \
   --germline_resource af-only-gnomad.vcf.gz \
   --normal_panel pon.vcf.gz \
   -L intervals.list \
   -O tumor_matched_m2_snvs_indels.vcf.gz
 

Single tumor sample

  gatk-launch --javaOptions "-Xmx4g" Mutect2 \
   -R ref_fasta.fa \
   -I tumor.bam \
   -tumor tumor_sample_name \
   --germline_resource af-only-gnomad.vcf.gz \
   --normal_panel pon.vcf.gz \
   -L intervals.list \
   -O tumor_unmatched_m2_snvs_indels.vcf.gz
 

Single normal sample for panel of normals (PoN) creation

To create a panel of normals (PoN), call on each normal sample as if a tumor sample. Then use CreateSomaticPanelOfNormals to output a PoN of germline and artifactual sites. This contrasts with the GATK3 workflow, which uses CombineVariants to retain variant sites called in at least two samples and then uses Picard MakeSitesOnlyVcf to simplify the callset for use as a PoN.

 gatk-launch --javaOptions "-Xmx4g" Mutect2 \
   -R ref_fasta.fa \
   -I normal1.bam \
   -tumor normal1_sample_name \
   --germline_resource af-only-gnomad.vcf.gz \
   -L intervals.list \
   -O normal1_for_pon.vcf.gz
 

Caveats

Although GATK4 Mutect2 is optimized to accomodate varying coverage depths, further optimization of parameters is necessary for extreme high depths, e.g. 1000X.


Additional Information

Read filters

These Read Filters are automatically applied to the data by the Engine before processing by Mutect2.

Mutect2 specific arguments

This table summarizes the command-line arguments that are specific to this tool. For more details on each argument, see the list further down below the table or click on an argument name to jump directly to that entry in the list.

Argument name(s) Default value Summary
Required Arguments
--input
 -I
[] BAM/SAM/CRAM file containing reads
--output
 -O
null File to which variants should be written
--reference
 -R
null Reference sequence file
--tumorSampleName
 -tumor
null BAM sample name of tumor
Optional Tool Arguments
--af_of_alleles_not_in_resource
 -default_af
0.001 Population allele fraction assigned to alleles not found in germline resource. A reasonable value is1/(2* number of samples in resource) if a germline resource is available; otherwise an average heterozygosity rate such as 0.001 is reasonable.
--alleles
null The set of alleles at which to genotype when --genotyping_mode is GENOTYPE_GIVEN_ALLELES
--annotateNDA
 -nda
false If provided, we will annotate records with the number of alternate alleles that were discovered (but not necessarily genotyped) at a given site
--annotation
 -A
[] One or more specific annotations to add to variant calls
--annotationGroup
 -G
[StandardMutectAnnotation] One or more groups of annotations to apply to variant calls
--annotationsToExclude
 -AX
[] One or more specific annotations to exclude from variant calls
--arguments_file
[] read one or more arguments files and add them to the command line
--assemblyRegionPadding
100 Number of additional bases of context to include around each assembly region
--base_quality_score_threshold
 -bqst
18 Base qualities below this threshold will be reduced to the minimum (6)
--cloudIndexPrefetchBuffer
 -CIPB
-1 Size of the cloud-only prefetch buffer (in MB; 0 to disable). Defaults to cloudPrefetchBuffer if unset.
--cloudPrefetchBuffer
 -CPB
40 Size of the cloud-only prefetch buffer (in MB; 0 to disable).
--contamination_fraction_to_filter
 -contamination
0.0 Fraction of contamination in sequencing data (for all samples) to aggressively remove
--dbsnp
 -D
null dbSNP file
--disableBamIndexCaching
 -DBIC
false If true, don't cache bam indexes, this will reduce memory requirements but may harm performance if many intervals are specified. Caching is automatically disabled if there are no intervals specified.
--gcs_max_retries
 -gcs_retries
20 If the GCS bucket channel errors out, how many times it will attempt to re-initiate the connection
--genotypePonSites
false Whether to call sites in the PoN even though they will ultimately be filtered.
--genotyping_mode
 -gt_mode
DISCOVERY Specifies how to determine the alternate alleles to use for genotyping
--germline_resource
null Population vcf of germline sequencing containing allele fractions.
--graphOutput
 -graph
null Write debug assembly graph information to this file
--help
 -h
false display the help message
--heterozygosity
 -hets
0.001 Heterozygosity value used to compute prior likelihoods for any locus. See the GATKDocs for full details on the meaning of this population genetics concept
--heterozygosity_stdev
 -heterozygosityStandardDeviation
0.01 Standard deviation of eterozygosity for SNP and indel calling.
--indel_heterozygosity
 -indelHeterozygosity
1.25E-4 Heterozygosity for indel calling. See the GATKDocs for heterozygosity for full details on the meaning of this population genetics concept
--initial_tumor_lod
2.0 LOD threshold to consider pileup active.
--interval_merging_rule
 -imr
ALL Interval merging rule for abutting intervals
--intervals
 -L
[] One or more genomic intervals over which to operate
--log_somatic_prior
-6.0 Prior probability that a given site has a somatic allele.
--max_population_af
0.01 Maximum population allele frequency in tumor-only mode.
--maxAssemblyRegionSize
300 Maximum size of an assembly region
--maxReadsPerAlignmentStart
50 Maximum number of reads to retain per alignment start position. Reads above this threshold will be downsampled. Set to 0 to disable.
--min_base_quality_score
 -mbq
10 Minimum base quality required to consider a base for calling
--minAssemblyRegionSize
50 Minimum size of an assembly region
--nativePairHmmThreads
 -threads
4 How many threads should a native pairHMM implementation use
--normal_lod
2.2 LOD threshold for calling normal variant non-germline.
--normal_panel
 -PON
null VCF file of sites observed in normal.
--normalSampleName
 -normal
null BAM sample name of tumor
--output_mode
 -out_mode
EMIT_VARIANTS_ONLY Specifies which type of calls we should output
--sample_ploidy
 -ploidy
2 Ploidy (number of chromosomes) per sample. For pooled data, set to (Number of samples in each pool * Sample Ploidy).
--standard_min_confidence_threshold_for_calling
 -stand_call_conf
10.0 The minimum phred-scaled confidence threshold at which variants should be called
--tumor_lod_to_emit
3.0 LOD threshold to emit tumor variant to VCF.
--useDoublePrecision
false use double precision in the native pairHmm. This is slower but matches the java implementation better
--useNewAFCalculator
 -newQual
false If provided, we will use the new AF model instead of the so-called exact model
--version
false display the version number for this tool
Optional Common Arguments
--addOutputSAMProgramRecord
true If true, adds a PG tag to created SAM/BAM/CRAM files.
--addOutputVCFCommandLine
true If true, adds a command line header line to created VCF files.
--createOutputBamIndex
 -OBI
true If true, create a BAM/CRAM index when writing a coordinate-sorted BAM/CRAM file.
--createOutputBamMD5
 -OBM
false If true, create a MD5 digest for any BAM/SAM/CRAM file created
--createOutputVariantIndex
 -OVI
true If true, create a VCF index when writing a coordinate-sorted VCF file.
--createOutputVariantMD5
 -OVM
false If true, create a a MD5 digest any VCF file created.
--disableReadFilter
 -DF
[] Read filters to be disabled before analysis
--disableSequenceDictionaryValidation
false If specified, do not check the sequence dictionaries from our inputs for compatibility. Use at your own risk!
--disableToolDefaultReadFilters
false Disable all tool default read filters
--excludeIntervals
 -XL
[] One or more genomic intervals to exclude from processing
--interval_exclusion_padding
 -ixp
0 Amount of padding (in bp) to add to each interval you are excluding.
--interval_padding
 -ip
0 Amount of padding (in bp) to add to each interval you are including.
--interval_set_rule
 -isr
UNION Set merging approach to use for combining interval inputs
--lenient
 -LE
false Lenient processing of VCF files
--QUIET
false Whether to suppress job-summary info on System.err.
--readFilter
 -RF
[] Read filters to be applied before analysis
--readIndex
[] Indices to use for the read inputs. If specified, an index must be provided for every read input and in the same order as the read inputs. If this argument is not specified, the path to the index for each input will be inferred automatically.
--readValidationStringency
 -VS
SILENT Validation stringency for all SAM/BAM/CRAM/SRA files read by this program. The default stringency value SILENT can improve performance when processing a BAM file in which variable-length data (read, qualities, tags) do not otherwise need to be decoded.
--secondsBetweenProgressUpdates
10.0 Output traversal statistics every time this many seconds elapse
--sequenceDictionary
null Use the given sequence dictionary as the master/canonical sequence dictionary. Must be a .dict file.
--TMP_DIR
[] Undocumented option
--use_jdk_deflater
 -jdk_deflater
false Whether to use the JdkDeflater (as opposed to IntelDeflater)
--use_jdk_inflater
 -jdk_inflater
false Whether to use the JdkInflater (as opposed to IntelInflater)
--verbosity
INFO Control verbosity of logging.
Advanced Arguments
--activeProbabilityThreshold
0.002 Minimum probability for a locus to be considered active.
--allowNonUniqueKmersInRef
false Allow graphs that have non-unique kmers in the reference
--allSitePLs
false Annotate all sites with PLs
--bamOutput
 -bamout
null File to which assembled haplotypes should be written
--bamWriterType
CALLED_HAPLOTYPES Which haplotypes should be written to the BAM
--comp
[] Comparison VCF file(s)
--consensus
false 1000G consensus mode
--contamination_fraction_per_sample_file
 -contaminationFile
null Tab-separated File containing fraction of contamination in sequencing data (per sample) to aggressively remove. Format should be "" (Contamination is double) per line; No header.
--debug
false Print out very verbose debug information about each triggering active region
--disableOptimizations
false Don't skip calculations in ActiveRegions with no variants
--doNotRunPhysicalPhasing
false Disable physical phasing
--dontIncreaseKmerSizesForCycles
false Disable iterating over kmer sizes when graph cycles are detected
--dontTrimActiveRegions
false If specified, we will not trim down the active region from the full region (active + extension) to just the active interval for genotyping
--dontUseSoftClippedBases
false Do not analyze soft clipped bases in the reads
--emitRefConfidence
 -ERC
NONE Mode for emitting reference confidence scores
--gcpHMM
10 Flat gap continuation penalty for use in the Pair HMM
--input_prior
 -inputPrior
[] Input prior for calls
--kmerSize
[10, 25] Kmer size to use in the read threading assembler
--max_alternate_alleles
 -maxAltAlleles
6 Maximum number of alternate alleles to genotype
--max_genotype_count
 -maxGT
1024 Maximum number of genotypes to consider at any site
--maxNumHaplotypesInPopulation
128 Maximum number of haplotypes to consider for your population
--maxProbPropagationDistance
50 Upper limit on how many bases away probability mass can be moved around when calculating the boundaries between active and inactive assembly regions
--minDanglingBranchLength
4 Minimum length of a dangling branch to attempt recovery
--minPruning
2 Minimum support to not prune paths in the graph
--numPruningSamples
1 Number of samples that must pass the minPruning threshold
--pcr_indel_model
 -pcrModel
CONSERVATIVE The PCR indel model to use
--phredScaledGlobalReadMismappingRate
 -globalMAPQ
45 The global assumed mismapping rate for reads
--readShardPadding
100 Each read shard has this many bases of extra context on each side. Read shards must have as much or more padding than assembly regions.
--readShardSize
-1 Maximum size of each read shard, in bases. Set to -1 for one shard per interval (or one shard per contig, if intervals are not explicitly specified). For good performance, this should typically be much larger than the maximum assembly region size.
--showHidden
false display hidden arguments
--smithWaterman
FASTEST_AVAILABLE Which Smith-Waterman implementation to use, generally FASTEST_AVAILABLE is the right choice
--useFilteredReadsForAnnotations
false Use the contamination-filtered read maps for the purposes of annotating variants
Deprecated Arguments
--recoverDanglingHeads
false This argument is deprecated since version 3.3

Argument details

Arguments in this list are specific to this tool. Keep in mind that other arguments are available that are shared with other tools (e.g. command-line GATK arguments); see Inherited arguments above.


--activeProbabilityThreshold / -activeProbabilityThreshold

Minimum probability for a locus to be considered active.

double  0.002  [ [ -∞  ∞ ] ]


--addOutputSAMProgramRecord / -addOutputSAMProgramRecord

If true, adds a PG tag to created SAM/BAM/CRAM files.

boolean  true


--addOutputVCFCommandLine / -addOutputVCFCommandLine

If true, adds a command line header line to created VCF files.

boolean  true


--af_of_alleles_not_in_resource / -default_af

Population allele fraction assigned to alleles not found in germline resource. A reasonable value is1/(2* number of samples in resource) if a germline resource is available; otherwise an average heterozygosity rate such as 0.001 is reasonable.
Population allele fraction assigned to alleles not found in germline resource.

double  0.001  [ [ -∞  ∞ ] ]


--alleles / -alleles

The set of alleles at which to genotype when --genotyping_mode is GENOTYPE_GIVEN_ALLELES
When the caller is put into GENOTYPE_GIVEN_ALLELES mode it will genotype the samples using only the alleles provide in this rod binding

FeatureInput[VariantContext]  null


--allowNonUniqueKmersInRef / -allowNonUniqueKmersInRef

Allow graphs that have non-unique kmers in the reference
By default, the program does not allow processing of reference sections that contain non-unique kmers. Disabling this check may cause problems in the assembly graph.

boolean  false


--allSitePLs / -allSitePLs

Annotate all sites with PLs
Advanced, experimental argument: if SNP likelihood model is specified, and if EMIT_ALL_SITES output mode is set, when we set this argument then we will also emit PLs at all sites. This will give a measure of reference confidence and a measure of which alt alleles are more plausible (if any). WARNINGS: - This feature will inflate VCF file size considerably. - All SNP ALT alleles will be emitted with corresponding 10 PL values. - An error will be emitted if EMIT_ALL_SITES is not set, or if anything other than diploid SNP model is used

boolean  false


--annotateNDA / -nda

If provided, we will annotate records with the number of alternate alleles that were discovered (but not necessarily genotyped) at a given site
Depending on the value of the --max_alternate_alleles argument, we may genotype only a fraction of the alleles being sent on for genotyping. Using this argument instructs the genotyper to annotate (in the INFO field) the number of alternate alleles that were originally discovered at the site.

boolean  false


--annotation / -A

One or more specific annotations to add to variant calls
Which annotations to include in variant calls in the output. These supplement annotations provided by annotation groups.

List[String]  []


--annotationGroup / -G

One or more groups of annotations to apply to variant calls
Which groups of annotations to add to the output variant calls. Any requirements that are not met (e.g. failing to provide a pedigree file for a pedigree-based annotation) may cause the run to fail.

List[String]  [StandardMutectAnnotation]


--annotationsToExclude / -AX

One or more specific annotations to exclude from variant calls
Which annotations to exclude from output in the variant calls. Note that this argument has higher priority than the -A or -G arguments, so these annotations will be excluded even if they are explicitly included with the other options.

List[String]  []


--arguments_file / NA

read one or more arguments files and add them to the command line

List[File]  []


--assemblyRegionPadding / -assemblyRegionPadding

Number of additional bases of context to include around each assembly region

int  100  [ [ -∞  ∞ ] ]


--bamOutput / -bamout

File to which assembled haplotypes should be written
The assembled haplotypes and locally realigned reads will be written as BAM to this file if requested. Really for debugging purposes only. Note that the output here does not include uninformative reads so that not every input read is emitted to the bam. Turning on this mode may result in serious performance cost for the caller. It's really only appropriate to use in specific areas where you want to better understand why the caller is making specific calls. The reads are written out containing an "HC" tag (integer) that encodes which haplotype each read best matches according to the haplotype caller's likelihood calculation. The use of this tag is primarily intended to allow good coloring of reads in IGV. Simply go to "Color Alignments By > Tag" and enter "HC" to more easily see which reads go with these haplotype. Note that the haplotypes (called or all, depending on mode) are emitted as single reads covering the entire active region, coming from sample "HC" and a special read group called "ArtificialHaplotype". This will increase the pileup depth compared to what would be expected from the reads only, especially in complex regions. Note also that only reads that are actually informative about the haplotypes are emitted. By informative we mean that there's a meaningful difference in the likelihood of the read coming from one haplotype compared to its next best haplotype. If multiple BAMs are passed as input to the tool (as is common for M2), then they will be combined in the bamout output and tagged with the appropriate sample names. The best way to visualize the output of this mode is with IGV. Tell IGV to color the alignments by tag, and give it the "HC" tag, so you can see which reads support each haplotype. Finally, you can tell IGV to group by sample, which will separate the potential haplotypes from the reads. All of this can be seen in this screenshot

String  null


--bamWriterType / -bamWriterType

Which haplotypes should be written to the BAM
The type of BAM output we want to see. This determines whether HC will write out all of the haplotypes it considered (top 128 max) or just the ones that were selected as alleles and assigned to samples.

The --bamWriterType argument is an enumerated type (WriterType), which can have one of the following values:

ALL_POSSIBLE_HAPLOTYPES
A mode that's for method developers. Writes out all of the possible haplotypes considered, as well as reads aligned to each
CALLED_HAPLOTYPES
A mode for users. Writes out the reads aligned only to the called haplotypes. Useful to understand why the caller is calling what it is

WriterType  CALLED_HAPLOTYPES


--base_quality_score_threshold / -bqst

Base qualities below this threshold will be reduced to the minimum (6)
Bases with a quality below this threshold will reduced to the minimum usable qualiy score (6).

byte  18  [ [ -∞  ∞ ] ]


--cloudIndexPrefetchBuffer / -CIPB

Size of the cloud-only prefetch buffer (in MB; 0 to disable). Defaults to cloudPrefetchBuffer if unset.

int  -1  [ [ -∞  ∞ ] ]


--cloudPrefetchBuffer / -CPB

Size of the cloud-only prefetch buffer (in MB; 0 to disable).

int  40  [ [ -∞  ∞ ] ]


--comp / -comp

Comparison VCF file(s)
If a call overlaps with a record from the provided comp track, the INFO field will be annotated as such in the output with the track name (e.g. -comp:FOO will have 'FOO' in the INFO field). Records that are filtered in the comp track will be ignored. Note that 'dbSNP' has been special-cased (see the --dbsnp argument).

List[FeatureInput[VariantContext]]  []


--consensus / -consensus

1000G consensus mode
This argument is specifically intended for 1000G consensus analysis mode. Setting this flag will inject all provided alleles to the assembly graph but will not forcibly genotype all of them.

boolean  false


--contamination_fraction_per_sample_file / -contaminationFile

Tab-separated File containing fraction of contamination in sequencing data (per sample) to aggressively remove. Format should be "" (Contamination is double) per line; No header.
This argument specifies a file with two columns "sample" and "contamination" specifying the contamination level for those samples. Samples that do not appear in this file will be processed with CONTAMINATION_FRACTION.

File  null


--contamination_fraction_to_filter / -contamination

Fraction of contamination in sequencing data (for all samples) to aggressively remove
If this fraction is greater is than zero, the caller will aggressively attempt to remove contamination through biased down-sampling of reads. Basically, it will ignore the contamination fraction of reads for each alternate allele. So if the pileup contains N total bases, then we will try to remove (N * contamination fraction) bases for each alternate allele.

double  0.0  [ [ -∞  ∞ ] ]


--createOutputBamIndex / -OBI

If true, create a BAM/CRAM index when writing a coordinate-sorted BAM/CRAM file.

boolean  true


--createOutputBamMD5 / -OBM

If true, create a MD5 digest for any BAM/SAM/CRAM file created

boolean  false


--createOutputVariantIndex / -OVI

If true, create a VCF index when writing a coordinate-sorted VCF file.

boolean  true


--createOutputVariantMD5 / -OVM

If true, create a a MD5 digest any VCF file created.

boolean  false


--dbsnp / -D

dbSNP file
rsIDs from this file are used to populate the ID column of the output. Also, the DB INFO flag will be set when appropriate. dbSNP is not used in any way for the calculations themselves.

FeatureInput[VariantContext]  null


--debug / -debug

Print out very verbose debug information about each triggering active region

boolean  false


--disableBamIndexCaching / -DBIC

If true, don't cache bam indexes, this will reduce memory requirements but may harm performance if many intervals are specified. Caching is automatically disabled if there are no intervals specified.

boolean  false


--disableOptimizations / -disableOptimizations

Don't skip calculations in ActiveRegions with no variants
If set, certain "early exit" optimizations in HaplotypeCaller, which aim to save compute and time by skipping calculations if an ActiveRegion is determined to contain no variants, will be disabled. This is most likely to be useful if you're using the -bamout argument to examine the placement of reads following reassembly and are interested in seeing the mapping of reads in regions with no variations. Setting the -forceActive and -dontTrimActiveRegions flags may also be necessary.

boolean  false


--disableReadFilter / -DF

Read filters to be disabled before analysis

List[String]  []


--disableSequenceDictionaryValidation / -disableSequenceDictionaryValidation

If specified, do not check the sequence dictionaries from our inputs for compatibility. Use at your own risk!

boolean  false


--disableToolDefaultReadFilters / -disableToolDefaultReadFilters

Disable all tool default read filters

boolean  false


--doNotRunPhysicalPhasing / -doNotRunPhysicalPhasing

Disable physical phasing
As of GATK 3.3, HaplotypeCaller outputs physical (read-based) information (see version 3.3 release notes and documentation for details). This argument disables that behavior.

boolean  false


--dontIncreaseKmerSizesForCycles / -dontIncreaseKmerSizesForCycles

Disable iterating over kmer sizes when graph cycles are detected
When graph cycles are detected, the normal behavior is to increase kmer sizes iteratively until the cycles are resolved. Disabling this behavior may cause the program to give up on assembling the ActiveRegion.

boolean  false


--dontTrimActiveRegions / -dontTrimActiveRegions

If specified, we will not trim down the active region from the full region (active + extension) to just the active interval for genotyping

boolean  false


--dontUseSoftClippedBases / -dontUseSoftClippedBases

Do not analyze soft clipped bases in the reads

boolean  false


--emitRefConfidence / -ERC

Mode for emitting reference confidence scores
The reference confidence mode makes it possible to emit a per-bp or summarized confidence estimate for a site being strictly homozygous-reference. See http://www.broadinstitute.org/gatk/guide/article?id=2940 for more details of how this works. Note that if you set -ERC GVCF, you also need to set -variant_index_type LINEAR and -variant_index_parameter 128000 (with those exact values!). This requirement is a temporary workaround for an issue with index compression.

The --emitRefConfidence argument is an enumerated type (ReferenceConfidenceMode), which can have one of the following values:

NONE
Regular calling without emitting reference confidence calls.
BP_RESOLUTION
Reference model emitted site by site.
GVCF
Reference model emitted with condensed non-variant blocks, i.e. the GVCF format.

ReferenceConfidenceMode  NONE


--excludeIntervals / -XL

One or more genomic intervals to exclude from processing
Use this argument to exclude certain parts of the genome from the analysis (like -L, but the opposite). This argument can be specified multiple times. You can use samtools-style intervals either explicitly on the command line (e.g. -XL 1 or -XL 1:100-200) or by loading in a file containing a list of intervals (e.g. -XL myFile.intervals).

List[String]  []


--gcpHMM / -gcpHMM

Flat gap continuation penalty for use in the Pair HMM

int  10  [ [ -∞  ∞ ] ]


--gcs_max_retries / -gcs_retries

If the GCS bucket channel errors out, how many times it will attempt to re-initiate the connection

int  20  [ [ -∞  ∞ ] ]


--genotypePonSites / NA

Whether to call sites in the PoN even though they will ultimately be filtered.
Usually we exclude sites in the panel of normals from active region determination, which saves time. Setting this to true causes Mutect to produce a variant call at these sites. This call will still be filtered, but it shows up in the vcf.

boolean  false


--genotyping_mode / -gt_mode

Specifies how to determine the alternate alleles to use for genotyping

The --genotyping_mode argument is an enumerated type (GenotypingOutputMode), which can have one of the following values:

DISCOVERY
The genotyper will choose the most likely alternate allele
GENOTYPE_GIVEN_ALLELES
Only the alleles passed by the user should be considered.

GenotypingOutputMode  DISCOVERY


--germline_resource / NA

Population vcf of germline sequencing containing allele fractions.
A resource, such as gnomAD, containing population allele frequencies of common and rare variants.

FeatureInput[VariantContext]  null


--graphOutput / -graph

Write debug assembly graph information to this file
This argument is meant for debugging and is not immediately useful for normal analysis use.

String  null


--help / -h

display the help message

boolean  false


--heterozygosity / -hets

Heterozygosity value used to compute prior likelihoods for any locus. See the GATKDocs for full details on the meaning of this population genetics concept
The expected heterozygosity value used to compute prior probability that a locus is non-reference. The default priors are for provided for humans: het = 1e-3 which means that the probability of N samples being hom-ref at a site is: 1 - sum_i_2N (het / i) Note that heterozygosity as used here is the population genetics concept: http://en.wikipedia.org/wiki/Zygosity#Heterozygosity_in_population_genetics That is, a hets value of 0.01 implies that two randomly chosen chromosomes from the population of organisms would differ from each other (one being A and the other B) at a rate of 1 in 100 bp. Note that this quantity has nothing to do with the likelihood of any given sample having a heterozygous genotype, which in the GATK is purely determined by the probability of the observed data P(D | AB) under the model that there may be a AB het genotype. The posterior probability of this AB genotype would use the het prior, but the GATK only uses this posterior probability in determining the prob. that a site is polymorphic. So changing the het parameters only increases the chance that a site will be called non-reference across all samples, but doesn't actually change the output genotype likelihoods at all, as these aren't posterior probabilities at all. The quantity that changes whether the GATK considers the possibility of a het genotype at all is the ploidy, which determines how many chromosomes each individual in the species carries.

Double  0.001  [ [ -∞  ∞ ] ]


--heterozygosity_stdev / -heterozygosityStandardDeviation

Standard deviation of eterozygosity for SNP and indel calling.
The standard deviation of the distribution of alt allele fractions. The above heterozygosity parameters give the *mean* of this distribution; this parameter gives its spread.

double  0.01  [ [ -∞  ∞ ] ]


--indel_heterozygosity / -indelHeterozygosity

Heterozygosity for indel calling. See the GATKDocs for heterozygosity for full details on the meaning of this population genetics concept
This argument informs the prior probability of having an indel at a site.

double  1.25E-4  [ [ -∞  ∞ ] ]


--initial_tumor_lod / NA

LOD threshold to consider pileup active.
Only variants with estimated tumor LODs exceeding this threshold will be considered active.

double  2.0  [ [ -∞  ∞ ] ]


--input / -I

BAM/SAM/CRAM file containing reads

R List[String]  []


--input_prior / -inputPrior

Input prior for calls
By default, the prior specified with the argument --heterozygosity/-hets is used for variant discovery at a particular locus, using an infinite sites model, see e.g. Waterson (1975) or Tajima (1996). This model asserts that the probability of having a population of k variant sites in N chromosomes is proportional to theta/k, for 1=1:N There are instances where using this prior might not be desireable, e.g. for population studies where prior might not be appropriate, as for example when the ancestral status of the reference allele is not known. By using this argument, user can manually specify priors to be used for calling as a vector for doubles, with the following restriciotns: a) User must specify 2N values, where N is the number of samples. b) Only diploid calls supported. c) Probability values are specified in double format, in linear space. d) No negative values allowed. e) Values will be added and Pr(AC=0) will be 1-sum, so that they sum up to one. f) If user-defined values add to more than one, an error will be produced. If user wants completely flat priors, then user should specify the same value (=1/(2*N+1)) 2*N times,e.g. -inputPrior 0.33 -inputPrior 0.33 for the single-sample diploid case.

List[Double]  []


--interval_exclusion_padding / -ixp

Amount of padding (in bp) to add to each interval you are excluding.
Use this to add padding to the intervals specified using -XL. For example, '-XL 1:100' with a padding value of 20 would turn into '-XL 1:80-120'. This is typically used to add padding around targets when analyzing exomes.

int  0  [ [ -∞  ∞ ] ]


--interval_merging_rule / -imr

Interval merging rule for abutting intervals
By default, the program merges abutting intervals (i.e. intervals that are directly side-by-side but do not actually overlap) into a single continuous interval. However you can change this behavior if you want them to be treated as separate intervals instead.

The --interval_merging_rule argument is an enumerated type (IntervalMergingRule), which can have one of the following values:

ALL
OVERLAPPING_ONLY

IntervalMergingRule  ALL


--interval_padding / -ip

Amount of padding (in bp) to add to each interval you are including.
Use this to add padding to the intervals specified using -L. For example, '-L 1:100' with a padding value of 20 would turn into '-L 1:80-120'. This is typically used to add padding around targets when analyzing exomes.

int  0  [ [ -∞  ∞ ] ]


--interval_set_rule / -isr

Set merging approach to use for combining interval inputs
By default, the program will take the UNION of all intervals specified using -L and/or -XL. However, you can change this setting for -L, for example if you want to take the INTERSECTION of the sets instead. E.g. to perform the analysis only on chromosome 1 exomes, you could specify -L exomes.intervals -L 1 --interval_set_rule INTERSECTION. However, it is not possible to modify the merging approach for intervals passed using -XL (they will always be merged using UNION). Note that if you specify both -L and -XL, the -XL interval set will be subtracted from the -L interval set.

The --interval_set_rule argument is an enumerated type (IntervalSetRule), which can have one of the following values:

UNION
Take the union of all intervals
INTERSECTION
Take the intersection of intervals (the subset that overlaps all intervals specified)

IntervalSetRule  UNION


--intervals / -L

One or more genomic intervals over which to operate

List[String]  []


--kmerSize / -kmerSize

Kmer size to use in the read threading assembler
Multiple kmer sizes can be specified, using e.g. `-kmerSize 10 -kmerSize 25`.

List[Integer]  [10, 25]


--lenient / -LE

Lenient processing of VCF files

boolean  false


--log_somatic_prior / NA

Prior probability that a given site has a somatic allele.
Prior log-10 probability that any given site has a somatic allele. Impacts germline probability calculation. The workflow uses this parameter only towards the germline event filter. It does NOT relate to the LOD threshold. For example, -6 translates to one in a million or ~3000 somatic mutations per human genome. Depending on tumor type, mutation rate ranges vary (Lawrence et al. Nature 2013), and so adjust parameter accordingly. For higher expected rate of mutation, adjust number up, e.g. -5. For lower expected rate of mutation, adjust number down, e.g. -7.

double  -6.0  [ [ -∞  ∞ ] ]


--max_alternate_alleles / -maxAltAlleles

Maximum number of alternate alleles to genotype
If there are more than this number of alternate alleles presented to the genotyper (either through discovery or GENOTYPE_GIVEN ALLELES), then only this many alleles will be used. Note that genotyping sites with many alternate alleles is both CPU and memory intensive and it scales exponentially based on the number of alternate alleles. Unless there is a good reason to change the default value, we highly recommend that you not play around with this parameter. See also {@link #MAX_GENOTYPE_COUNT}.

int  6  [ [ -∞  ∞ ] ]


--max_genotype_count / -maxGT

Maximum number of genotypes to consider at any site
If there are more than this number of genotypes at a locus presented to the genotyper, then only this many genotypes will be used. The possible genotypes are simply different ways of partitioning alleles given a specific ploidy asumption. Therefore, we remove genotypes from consideration by removing alternate alleles that are the least well supported. The estimate of allele support is based on the ranking of the candidate haplotypes coming out of the graph building step. Note that the reference allele is always kept. Note that genotyping sites with large genotype counts is both CPU and memory intensive. Unless there is a good reason to change the default value, we highly recommend that you not play around with this parameter. The maximum number of alternative alleles used in the genotyping step will be the lesser of the two: 1. the largest number of alt alleles, given ploidy, that yields a genotype count no higher than {@link #MAX_GENOTYPE_COUNT} 2. the value of {@link #MAX_ALTERNATE_ALLELES} See also {@link #MAX_ALTERNATE_ALLELES}.

int  1024  [ [ -∞  ∞ ] ]


--max_population_af / NA

Maximum population allele frequency in tumor-only mode.
In tumor-only mode, we discard variants with population allele frequencies greater than this threshold.

double  0.01  [ [ -∞  ∞ ] ]


--maxAssemblyRegionSize / -maxAssemblyRegionSize

Maximum size of an assembly region

int  300  [ [ -∞  ∞ ] ]


--maxNumHaplotypesInPopulation / -maxNumHaplotypesInPopulation

Maximum number of haplotypes to consider for your population
The assembly graph can be quite complex, and could imply a very large number of possible haplotypes. Each haplotype considered requires N PairHMM evaluations if there are N reads across all samples. In order to control the run of the haplotype caller we only take maxNumHaplotypesInPopulation paths from the graph, in order of their weights, no matter how many paths are possible to generate from the graph. Putting this number too low will result in dropping true variation because paths that include the real variant are not even considered. You can consider increasing this number when calling organisms with high heterozygosity.

int  128  [ [ -∞  ∞ ] ]


--maxProbPropagationDistance / -maxProbPropagationDistance

Upper limit on how many bases away probability mass can be moved around when calculating the boundaries between active and inactive assembly regions

int  50  [ [ -∞  ∞ ] ]


--maxReadsPerAlignmentStart / -maxReadsPerAlignmentStart

Maximum number of reads to retain per alignment start position. Reads above this threshold will be downsampled. Set to 0 to disable.

int  50  [ [ -∞  ∞ ] ]


--min_base_quality_score / -mbq

Minimum base quality required to consider a base for calling
Bases with a quality below this threshold will not be used for calling.

byte  10  [ [ -∞  ∞ ] ]


--minAssemblyRegionSize / -minAssemblyRegionSize

Minimum size of an assembly region

int  50  [ [ -∞  ∞ ] ]


--minDanglingBranchLength / -minDanglingBranchLength

Minimum length of a dangling branch to attempt recovery
When constructing the assembly graph we are often left with "dangling" branches. The assembly engine attempts to rescue these branches by merging them back into the main graph. This argument describes the minimum length of a dangling branch needed for the engine to try to rescue it. A smaller number here will lead to higher sensitivity to real variation but also to a higher number of false positives.

int  4  [ [ -∞  ∞ ] ]


--minPruning / -minPruning

Minimum support to not prune paths in the graph
Paths with fewer supporting kmers than the specified threshold will be pruned from the graph. Be aware that this argument can dramatically affect the results of variant calling and should only be used with great caution. Using a prune factor of 1 (or below) will prevent any pruning from the graph, which is generally not ideal; it can make the calling much slower and even less accurate (because it can prevent effective merging of "tails" in the graph). Higher values tend to make the calling much faster, but also lowers the sensitivity of the results (because it ultimately requires higher depth to produce calls).

int  2  [ [ -∞  ∞ ] ]


--nativePairHmmThreads / -threads

How many threads should a native pairHMM implementation use

int  4  [ [ -∞  ∞ ] ]


--normal_lod / NA

LOD threshold for calling normal variant non-germline.
This is a measure of the minimum evidence to support that a variant observed in the tumor is not also present in the normal. Applies to normal data in a tumor with matched normal analysis. The default has been tuned for diploid somatic analyses. It is unlikely such analyses will require changing the default value. Increasing the parameter may increase the sensitivity of somatic calling, but may also increase calling false positive, i.e. germline, variants.

double  2.2  [ [ -∞  ∞ ] ]


--normal_panel / -PON

VCF file of sites observed in normal.
A panel of normals can be a useful (optional) input to help filter out commonly seen sequencing noise that may appear as low allele-fraction somatic variants.

FeatureInput[VariantContext]  null


--normalSampleName / -normal

BAM sample name of tumor

String  null


--numPruningSamples / -numPruningSamples

Number of samples that must pass the minPruning threshold
If fewer samples than the specified number pass the minPruning threshold for a given path, that path will be eliminated from the graph.

int  1  [ [ -∞  ∞ ] ]


--output / -O

File to which variants should be written

R File  null


--output_mode / -out_mode

Specifies which type of calls we should output

The --output_mode argument is an enumerated type (OutputMode), which can have one of the following values:

EMIT_VARIANTS_ONLY
produces calls only at variant sites
EMIT_ALL_CONFIDENT_SITES
produces calls at variant sites and confident reference sites
EMIT_ALL_SITES
produces calls at any callable site regardless of confidence; this argument is intended only for point mutations (SNPs) in DISCOVERY mode or generally when running in GENOTYPE_GIVEN_ALLELES mode; it will by no means produce a comprehensive set of indels in DISCOVERY mode

OutputMode  EMIT_VARIANTS_ONLY


--pcr_indel_model / -pcrModel

The PCR indel model to use
When calculating the likelihood of variants, we can try to correct for PCR errors that cause indel artifacts. The correction is based on the reference context, and acts specifically around repetitive sequences that tend to cause PCR errors). The variant likelihoods are penalized in increasing scale as the context around a putative indel is more repetitive (e.g. long homopolymer). The correction can be disabling by specifying '-pcrModel NONE'; in that case the default base insertion/deletion qualities will be used (or taken from the read if generated through the BaseRecalibrator). VERY IMPORTANT: when using PCR-free sequencing data we definitely recommend setting this argument to NONE.

The --pcr_indel_model argument is an enumerated type (PCRErrorModel), which can have one of the following values:

NONE
no specialized PCR error model will be applied; if base insertion/deletion qualities are present they will be used
HOSTILE
a most aggressive model will be applied that sacrifices true positives in order to remove more false positives
AGGRESSIVE
a more aggressive model will be applied that sacrifices true positives in order to remove more false positives
CONSERVATIVE
a less aggressive model will be applied that tries to maintain a high true positive rate at the expense of allowing more false positives

PCRErrorModel  CONSERVATIVE


--phredScaledGlobalReadMismappingRate / -globalMAPQ

The global assumed mismapping rate for reads
The phredScaledGlobalReadMismappingRate reflects the average global mismapping rate of all reads, regardless of their mapping quality. This term effects the probability that a read originated from the reference haplotype, regardless of its edit distance from the reference, in that the read could have originated from the reference haplotype but from another location in the genome. Suppose a read has many mismatches from the reference, say like 5, but has a very high mapping quality of 60. Without this parameter, the read would contribute 5 * Q30 evidence in favor of its 5 mismatch haplotype compared to reference, potentially enough to make a call off that single read for all of these events. With this parameter set to Q30, though, the maximum evidence against any haplotype that this (and any) read could contribute is Q30. Set this term to any negative number to turn off the global mapping rate.

int  45  [ [ -∞  ∞ ] ]


--QUIET / NA

Whether to suppress job-summary info on System.err.

Boolean  false


--readFilter / -RF

Read filters to be applied before analysis

List[String]  []


--readIndex / -readIndex

Indices to use for the read inputs. If specified, an index must be provided for every read input and in the same order as the read inputs. If this argument is not specified, the path to the index for each input will be inferred automatically.

List[String]  []


--readShardPadding / -readShardPadding

Each read shard has this many bases of extra context on each side. Read shards must have as much or more padding than assembly regions.

int  100  [ [ -∞  ∞ ] ]


--readShardSize / -readShardSize

Maximum size of each read shard, in bases. Set to -1 for one shard per interval (or one shard per contig, if intervals are not explicitly specified). For good performance, this should typically be much larger than the maximum assembly region size.

int  -1  [ [ -∞  ∞ ] ]


--readValidationStringency / -VS

Validation stringency for all SAM/BAM/CRAM/SRA files read by this program. The default stringency value SILENT can improve performance when processing a BAM file in which variable-length data (read, qualities, tags) do not otherwise need to be decoded.

The --readValidationStringency argument is an enumerated type (ValidationStringency), which can have one of the following values:

STRICT
LENIENT
SILENT

ValidationStringency  SILENT


--recoverDanglingHeads / -recoverDanglingHeads

This argument is deprecated since version 3.3
As of version 3.3, this argument is no longer needed because dangling end recovery is now the default behavior. See GATK 3.3 release notes for more details.

boolean  false


--reference / -R

Reference sequence file

R String  null


--sample_ploidy / -ploidy

Ploidy (number of chromosomes) per sample. For pooled data, set to (Number of samples in each pool * Sample Ploidy).
Sample ploidy - equivalent to number of chromosomes per pool. In pooled experiments this should be = # of samples in pool * individual sample ploidy

int  2  [ [ -∞  ∞ ] ]


--secondsBetweenProgressUpdates / -secondsBetweenProgressUpdates

Output traversal statistics every time this many seconds elapse

double  10.0  [ [ -∞  ∞ ] ]


--sequenceDictionary / -sequenceDictionary

Use the given sequence dictionary as the master/canonical sequence dictionary. Must be a .dict file.

String  null


--showHidden / -showHidden

display hidden arguments

boolean  false


--smithWaterman / -smithWaterman

Which Smith-Waterman implementation to use, generally FASTEST_AVAILABLE is the right choice

The --smithWaterman argument is an enumerated type (Implementation), which can have one of the following values:

FASTEST_AVAILABLE
use the fastest Smith-Waterman aligner that runs on your hardware
JAVA
use the pure java implementation of Smith-Waterman, works on all hardware

Implementation  FASTEST_AVAILABLE


--standard_min_confidence_threshold_for_calling / -stand_call_conf

The minimum phred-scaled confidence threshold at which variants should be called
The minimum phred-scaled confidence threshold at which variants should be called. Only variant sites with QUAL equal or greater than this threshold will be called. Note that since version 3.7, we no longer differentiate high confidence from low confidence calls at the calling step. The default call confidence threshold is set low intentionally to achieve high sensitivity, which will allow false positive calls as a side effect. Be sure to perform some kind of filtering after calling to reduce the amount of false positives in your final callset. Note that when HaplotypeCaller is used in GVCF mode (using either -ERC GVCF or -ERC BP_RESOLUTION) the call threshold is automatically set to zero. Call confidence thresholding will then be performed in the subsequent GenotypeGVCFs command.

double  10.0  [ [ -∞  ∞ ] ]


--TMP_DIR / NA

Undocumented option

List[File]  []


--tumor_lod_to_emit / NA

LOD threshold to emit tumor variant to VCF.
Only variants with tumor LODs exceeding this threshold will be written to the VCF, regardless of filter status. Set to less than or equal to tumor_lod. Increase argument value to reduce false positives in the callset. Default setting of 3 is permissive and will emit some amount of negative training data that {@link FilterMutectCalls} should then filter.

double  3.0  [ [ -∞  ∞ ] ]


--tumorSampleName / -tumor

BAM sample name of tumor

R String  null


--use_jdk_deflater / -jdk_deflater

Whether to use the JdkDeflater (as opposed to IntelDeflater)

boolean  false


--use_jdk_inflater / -jdk_inflater

Whether to use the JdkInflater (as opposed to IntelInflater)

boolean  false


--useDoublePrecision / -useDoublePrecision

use double precision in the native pairHmm. This is slower but matches the java implementation better

boolean  false


--useFilteredReadsForAnnotations / -useFilteredReadsForAnnotations

Use the contamination-filtered read maps for the purposes of annotating variants

boolean  false


--useNewAFCalculator / -newQual

If provided, we will use the new AF model instead of the so-called exact model
Use the new allele frequency / QUAL score model

boolean  false


--verbosity / -verbosity

Control verbosity of logging.

The --verbosity argument is an enumerated type (LogLevel), which can have one of the following values:

ERROR
WARNING
INFO
DEBUG

LogLevel  INFO


--version / NA

display the version number for this tool

boolean  false


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GATK version 4.beta.6-SNAPSHOT built at 26-38-2017 05:38:32.