Showing docs for version 3.7-0 | The latest version is 3.7-0


MuTect2

Call somatic SNPs and indels via local re-assembly of haplotypes

Category Variant Discovery Tools

Traversal ActiveRegionWalker

PartitionBy LOCUS


Overview

MuTect2 is a somatic SNP and indel caller that combines the DREAM challenge-winning somatic genotyping engine of the original MuTect (Cibulskis et al., 2013) with the assembly-based machinery of HaplotypeCaller. The basic operation of MuTect2 proceeds similarly to that of the HaplotypeCaller.

Differences from HaplotypeCaller

While the HaplotypeCaller relies on a ploidy assumption (diploid by default) to inform its genotype likelihood and variant quality calculations, MuTect2 allows for a varying allelic fraction for each variant, as is often seen in tumors with purity less than 100%, multiple subclones, and/or copy number variation (either local or aneuploidy). MuTect2 also differs from the HaplotypeCaller in that it does apply some hard filters to variants before producing output.

Note that the GVCF generation capabilities of HaplotypeCaller are NOT available in MuTect2, even though some of the relevant arguments are listed below. There are currently no plans to make GVCF calling available in MuTect2.

Usage examples

These are example commands that show how to run MuTect2 for typical use cases. Square brackets ("[ ]") indicate optional arguments. Note that parameter values shown here may not be the latest recommended; see the Best Practices documentation for detailed recommendations.


Tumor/Normal variant calling

   java -jar GenomeAnalysisTK.jar \
     -T MuTect2 \
     -R reference.fasta \
     -I:tumor tumor.bam \
     -I:normal normal.bam \
     [--dbsnp dbSNP.vcf] \
     [--cosmic COSMIC.vcf] \
     [-L targets.interval_list] \
     -o output.vcf
 

Normal-only calling for panel of normals creation

   java -jar GenomeAnalysisTK.jar \
     -T MuTect2 \
     -R reference.fasta \
     -I:tumor normal1.bam \
     [--dbsnp dbSNP.vcf] \
     [--cosmic COSMIC.vcf] \
     --artifact_detection_mode \
     [-L targets.interval_list] \
     -o output.normal1.vcf
 

For full PON creation, call each of your normals separately in artifact detection mode as shown above. Then use CombineVariants to output only sites where a variant was seen in at least two samples:
   java -jar GenomeAnalysisTK.jar \
     -T CombineVariants \
     -R reference.fasta \
     -V output.normal1.vcf -V output.normal2.vcf [-V output.normal2.vcf ...] \
     -minN 2 \
     --setKey "null" \
     --filteredAreUncalled \
     --filteredrecordsmergetype KEEP_IF_ANY_UNFILTERED \
     [-L targets.interval_list] \
     -o MuTect2_PON.vcf
 

Caveats

  • As noted in several places in the documentation, MuTect2 is currently released under BETA status; it is NOT recommended for production work and is NOT available for commercial/for-profit licensing.
  • MuTect2 currently only supports the calling of a single tumor-normal pair at a time.
  • Tumor-only variant calling is possible but it is NOT supported and we will not answer any questions about it until it becomes a supported feature.
  • Some of the arguments listed below are not functional; they are exclusive to HaplotypeCaller and are listed here due to technical entanglements in the code. This will be resolved in the upcoming GATK 4 release.

Additional Information

Read filters

These Read Filters are automatically applied to the data by the Engine before processing by MuTect2.

Parallelism options

This tool can be run in multi-threaded mode using this option.

Downsampling settings

This tool applies the following downsampling settings by default.

  • Mode: BY_SAMPLE
  • To coverage: 1,000

ActiveRegion settings

This tool uses ActiveRegions on the reference.

  • Minimum region size: 50 bp
  • Maximum region size: 300 bp
  • Extension increments: 100 bp

Command-line Arguments

Engine arguments

All tools inherit arguments from the GATK Engine' "CommandLineGATK" argument collection, which can be used to modify various aspects of the tool's function. For example, the -L argument directs the GATK engine to restrict processing to specific genomic intervals; or the -rf argument allows you to apply certain read filters to exclude some of the data from the analysis.

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
Optional Inputs
--alleles
none Set of alleles to use in genotyping
--cosmic
[] VCF file of COSMIC sites
--dbsnp
 -D
none dbSNP file
--normal_panel
 -PON
[] VCF file of sites observed in normal
Optional Outputs
--activeRegionOut
 -ARO
NA Output the active region to this IGV formatted file
--activityProfileOut
 -APO
NA Output the raw activity profile results in IGV format
--graphOutput
 -graph
NA Write debug assembly graph information to this file
--out
 -o
stdout File to which variants should be written
Optional Parameters
--contamination_fraction_to_filter
 -contamination
0.0 Fraction of contamination to aggressively remove
--dbsnp_normal_lod
5.5 LOD threshold for calling normal non-variant at dbsnp sites
--debug_read_name
NA trace this read name through the calling process
--genotyping_mode
 -gt_mode
DISCOVERY Specifies how to determine the alternate alleles to use for genotyping
--group
 -G
[] One or more classes/groups of annotations to apply to variant calls
--heterozygosity
 -hets
0.001 Heterozygosity value used to compute prior likelihoods for any locus
--heterozygosity_stdev
 -heterozygosityStandardDeviation
0.01 Standard deviation of eterozygosity for SNP and indel calling.
--indel_heterozygosity
 -indelHeterozygosity
1.25E-4 Heterozygosity for indel calling
--initial_normal_lod
0.5 Initial LOD threshold for calling normal variant
--initial_tumor_lod
4.0 Initial LOD threshold for calling tumor variant
--max_alt_allele_in_normal_fraction
0.03 Threshold for maximum alternate allele fraction in normal
--max_alt_alleles_in_normal_count
1 Threshold for maximum alternate allele counts in normal
--max_alt_alleles_in_normal_qscore_sum
20 Threshold for maximum alternate allele quality score sum in normal
--maxReadsInRegionPerSample
1000 Maximum reads in an active region
--min_base_quality_score
 -mbq
10 Minimum base quality required to consider a base for calling
--minReadsPerAlignmentStart
 -minReadsPerAlignStart
5 Minimum number of reads sharing the same alignment start for each genomic location in an active region
--normal_lod
2.2 LOD threshold for calling normal non-germline
--pir_mad_threshold
3.0 threshold for clustered read position artifact MAD
--pir_median_threshold
10.0 threshold for clustered read position artifact median
--power_constant_qscore
30 Phred scale quality score constant to use in power calculations
--sample_ploidy
 -ploidy
2 Ploidy 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
6.3 LOD threshold for calling tumor variant
Optional Flags
--annotateNDA
 -nda
false Annotate number of alleles observed
--enable_clustered_read_position_filter
false turn on clustered read position filter
--enable_strand_artifact_filter
false turn on strand artifact filter
--useNewAFCalculator
 -newQual
false Use new AF model instead of the so-called exact model
Advanced Inputs
--activeRegionIn
 -AR
NA Use this interval list file as the active regions to process
--comp
[] comparison VCF file
Advanced Outputs
--bamOutput
 -bamout
NA File to which assembled haplotypes should be written
Advanced Parameters
--activeProbabilityThreshold
 -ActProbThresh
0.002 Threshold for the probability of a profile state being active.
--activeRegionExtension
NA The active region extension; if not provided defaults to Walker annotated default
--activeRegionMaxSize
NA The active region maximum size; if not provided defaults to Walker annotated default
--annotation
 -A
[DepthPerAlleleBySample, BaseQualitySumPerAlleleBySample, TandemRepeatAnnotator, OxoGReadCounts] One or more specific annotations to apply to variant calls
--bamWriterType
CALLED_HAPLOTYPES Which haplotypes should be written to the BAM
--bandPassSigma
NA The sigma of the band pass filter Gaussian kernel; if not provided defaults to Walker annotated default
--contamination_fraction_per_sample_file
 -contaminationFile
NA Contamination per sample
--emitRefConfidence
 -ERC
NONE Mode for emitting reference confidence scores
--excludeAnnotation
 -XA
[SpanningDeletions] One or more specific annotations to exclude
--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
--max_num_PL_values
 -maxNumPLValues
100 Maximum number of PL values to output
--maxNumHaplotypesInPopulation
128 Maximum number of haplotypes to consider for your population
--maxReadsInMemoryPerSample
30000 Maximum reads per sample given to traversal map() function
--maxTotalReadsInMemory
10000000 Maximum total reads given to traversal map() function
--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
--output_mode
 -out_mode
EMIT_VARIANTS_ONLY Which type of calls we should output
--phredScaledGlobalReadMismappingRate
 -globalMAPQ
45 The global assumed mismapping rate for reads
Advanced Flags
--allowNonUniqueKmersInRef
false Allow graphs that have non-unique kmers in the reference
--allSitePLs
false Annotate all sites with PLs
--artifact_detection_mode
false Enable artifact detection for creating panels of normals
--consensus
false 1000G consensus mode
--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 If specified, we will not analyze soft clipped bases in the reads
--emitDroppedReads
 -edr
false Emit reads that are dropped for filtering, trimming, realignment failure
--forceActive
false If provided, all bases will be tagged as active
--m2debug
false Print out very verbose M2 debug information
--useFilteredReadsForAnnotations
false Use the contamination-filtered read maps for the purposes of annotating variants

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 / -ActProbThresh

Threshold for the probability of a profile state being active.

Double  0.002  [ [ 0  1 ] ]


--activeRegionExtension / -activeRegionExtension

The active region extension; if not provided defaults to Walker annotated default

Integer  NA


--activeRegionIn / -AR

Use this interval list file as the active regions to process

List[IntervalBinding[Feature]]  NA


--activeRegionMaxSize / -activeRegionMaxSize

The active region maximum size; if not provided defaults to Walker annotated default

Integer  NA


--activeRegionOut / -ARO

Output the active region to this IGV formatted file
If provided, this walker will write out its active and inactive regions to this file in the IGV formatted TAB deliminated output: http://www.broadinstitute.org/software/igv/IGV Intended to make debugging the active region calculations easier

PrintStream  NA


--activityProfileOut / -APO

Output the raw activity profile results in IGV format
If provided, this walker will write out its activity profile (per bp probabilities of being active) to this file in the IGV formatted TAB deliminated output: http://www.broadinstitute.org/software/igv/IGV Intended to make debugging the activity profile calculations easier

PrintStream  NA


--alleles / -alleles

Set of alleles to use in genotyping
When --genotyping_mode is set to GENOTYPE_GIVEN_ALLELES mode, the caller will genotype the samples using only the alleles provide in this callset. Note that this is not well tested in HaplotypeCaller, and is definitely not suitable for use with HaplotypeCaller in -ERC GVCF mode. In addition, it does not apply to MuTect2 at all.

This argument supports reference-ordered data (ROD) files in the following formats: BCF2, VCF, VCF3

RodBinding[VariantContext]  none


--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
Experimental argument FOR USE WITH UnifiedGenotyper ONLY: 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 - THIS WILL NOT WORK WITH HaplotypeCaller, GenotypeGVCFs or MuTect2! Use HaplotypeCaller with -ERC GVCF then GenotypeGVCFs instead. See the Best Practices documentation for more information.

boolean  false


--annotateNDA / -nda

Annotate number of alleles observed
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 (but not necessarily genotyped) at the site.

boolean  false


--annotation / -A

One or more specific annotations to apply to variant calls
Which annotations to add to the output VCF file. See the VariantAnnotator -list argument to view available annotations.

List[String]  [DepthPerAlleleBySample, BaseQualitySumPerAlleleBySample, TandemRepeatAnnotator, OxoGReadCounts]


--artifact_detection_mode / NA

Enable artifact detection for creating panels of normals
Artifact detection mode is used to prepare a panel of normals. This maintains the specified tumor LOD threshold, but disables the remaining pragmatic filters. See usage examples above for more information.

boolean  false


--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. This is intended to be used only for troubleshooting purposes, in specific areas where you want to better understand why the caller is making specific calls. Turning on this mode may result in serious performance cost for the caller, so we do NOT recommend using this argument systematically as it will significantly increase runtime. The candidate 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. 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. You can also tell IGV to group reads by sample, which will separate the potential haplotypes from the reads. These features are illustrated in this screenshot. Note that only reads that are actually informative about the haplotypes are emitted with the HC tag. By informative we mean that there's a meaningful difference in the likelihood of the read coming from one haplotype compared to the next best haplotype. When coloring reads by HC tag in IGV, uninformative reads will remain grey. Note also that not every input read is emitted to the bam in this mode. To include all trimmed, downsampled, filtered and uninformative reads, add the --emitDroppedReads argument. If multiple BAMs are passed as input to the tool (as is common for MuTect2), then they will be combined in the -bamout output and tagged with the appropriate sample names.

GATKSAMFileWriter  NA


--bamWriterType / -bamWriterType

Which haplotypes should be written to the BAM
The type of -bamout 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 (Type), 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

Type  CALLED_HAPLOTYPES


--bandPassSigma / -bandPassSigma

The sigma of the band pass filter Gaussian kernel; if not provided defaults to Walker annotated default

Double  NA


--comp / -comp

comparison VCF file
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).

This argument supports reference-ordered data (ROD) files in the following formats: BCF2, VCF, VCF3

List[RodBinding[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

Contamination per sample
This argument specifies a file with two columns "sample" and "contamination" (separated by a tab) specifying the contamination level for those samples (where contamination is given as a decimal number, not an integer) per line. There should be no header. Samples that do not appear in this file will be processed with CONTAMINATION_FRACTION.

File  NA


--contamination_fraction_to_filter / -contamination

Fraction of contamination 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 (for all samples). 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  [ [ -∞  ∞ ] ]


--cosmic / -cosmic

VCF file of COSMIC sites
MuTect2 has the ability to use COSMIC data in conjunction with dbSNP to adjust the threshold for evidence of a variant in the normal. If a variant is present in dbSNP, but not in COSMIC, then more evidence is required from the normal sample to prove the variant is not present in germline.

This argument supports reference-ordered data (ROD) files in the following formats: BCF2, VCF, VCF3

List[RodBinding[VariantContext]]  []


--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 overlap is only used to require more evidence of absence in the normal if the variant in question has been seen before in germline.

This argument supports reference-ordered data (ROD) files in the following formats: BCF2, VCF, VCF3

RodBinding[VariantContext]  none


--dbsnp_normal_lod / NA

LOD threshold for calling normal non-variant at dbsnp sites
The LOD threshold for the normal is typically made more strict if the variant has been seen in dbSNP (i.e. another normal sample). We thus require MORE evidence that a variant is NOT seen in this tumor's normal if it has been observed as a germline variant before.

double  5.5  [ [ -∞  ∞ ] ]


--debug / -debug

Print out very verbose debug information about each triggering active region

boolean  false


--debug_read_name / NA

trace this read name through the calling process

String  NA


--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 helpful.

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

If specified, we will not analyze soft clipped bases in the reads

boolean  false


--emitDroppedReads / -edr

Emit reads that are dropped for filtering, trimming, realignment failure
Determines whether dropped reads will be tracked and emitted when -bamout is specified. Use this in combination with a specific interval of interest to avoid accumulating a large number of reads in the -bamout file.

boolean  false


--emitRefConfidence / -ERC

Mode for emitting reference confidence scores
The reference confidence mode makes it possible to emit variant calls in GVCF format, which includes either a per-base pair (BP_RESOLUTION) or a summarized (GVCF) confidence estimate for each position 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 use -ERC to emit a GVCF or BP_RESOLUTION output, you either need to give the output file the extension .g.vcf or set the parameters -variant_index_type LINEAR and -variant_index_parameter 128000 (with those exact values!). This has to do 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


--enable_clustered_read_position_filter / NA

turn on clustered read position filter

boolean  false


--enable_strand_artifact_filter / NA

turn on strand artifact filter

boolean  false


--excludeAnnotation / -XA

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

List[String]  [SpanningDeletions]


--forceActive / -forceActive

If provided, all bases will be tagged as active
For the active region walker to treat all bases as active. Useful for debugging when you want to force something like the HaplotypeCaller to process a specific interval you provide the GATK

boolean  false


--gcpHMM / -gcpHMM

Flat gap continuation penalty for use in the Pair HMM

int  10  [ [ -∞  ∞ ] ]


--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


--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.

PrintStream  NA


--group / -G

One or more classes/groups of annotations to apply to variant calls
Which groups of annotations to add to the output VCF file. See the VariantAnnotator -list argument to view available groups.

String[]  []


--heterozygosity / -hets

Heterozygosity value used to compute prior likelihoods for any locus
The expected heterozygosity value used to compute prior probability that a locus is non-reference. See https://software.broadinstitute.org/gatk/documentation/article?id=8603 for more details.

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
This argument informs the prior probability of having an indel at a site.

double  1.25E-4  [ [ -∞  ∞ ] ]


--initial_normal_lod / NA

Initial LOD threshold for calling normal variant
This is the LOD threshold corresponding to the minimum amount of reference evidence in the normal for a variant to be considered somatic and emitted in the VCF

double  0.5  [ [ -∞  ∞ ] ]


--initial_tumor_lod / NA

Initial LOD threshold for calling tumor variant
This is the LOD threshold that a variant must pass in the tumor to be emitted to the VCF. Note that the variant may pass this threshold yet still be annotated as FILTERed based on other criteria.

double  4.0  [ [ -∞  ∞ ] ]


--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. However, there are instances where using this prior might not be desirable, 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. This argument allows you to manually specify a list of probabilities for each AC>1 to be used as priors for genotyping, with the following restrictions: only diploid calls are supported; you must specify 2 * N values where N is the number of samples; probability values must be positive and specified in Double format, in linear space (not log10 space nor Phred-scale); and all values must sume to 1. For completely flat priors, 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]  []


--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]


--m2debug / -m2debug

Print out very verbose M2 debug information

boolean  false


--max_alt_allele_in_normal_fraction / NA

Threshold for maximum alternate allele fraction in normal
This argument is used for the internal "alt_allele_in_normal" filter. A variant will PASS the filter if the value tested is lower or equal to the threshold value. It will FAIL the filter if the value tested is greater than the max threshold value.

double  0.03  [ [ -∞  ∞ ] ]


--max_alt_alleles_in_normal_count / NA

Threshold for maximum alternate allele counts in normal
This argument is used for the internal "alt_allele_in_normal" filter. A variant will PASS the filter if the value tested is lower or equal to the threshold value. It will FAIL the filter if the value tested is greater than the max threshold value.

int  1  [ [ -∞  ∞ ] ]


--max_alt_alleles_in_normal_qscore_sum / NA

Threshold for maximum alternate allele quality score sum in normal
This argument is used for the internal "alt_allele_in_normal" filter. A variant will PASS the filter if the value tested is lower or equal to the threshold value. It will FAIL the filter if the value tested is greater than the max threshold value.

int  20  [ [ -∞  ∞ ] ]


--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. This is intended to deal with sites where the combination of high ploidy and high alt allele count can lead to an explosion in the number of possible genotypes, with extreme adverse effects on runtime performance. How does it work? The possible genotypes are simply different ways of partitioning alleles given a specific ploidy assumption. 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 however that the reference allele is always kept. 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} As noted above, genotyping sites with large genotype counts is both CPU and memory intensive. Unless you have a good reason to change the default value, we highly recommend that you not play around with this parameter. See also {@link #MAX_ALTERNATE_ALLELES}.

int  1024  [ [ -∞  ∞ ] ]


--max_num_PL_values / -maxNumPLValues

Maximum number of PL values to output
Determines the maximum number of PL values that will be logged in the output. If the number of genotypes (which is determined by the ploidy and the number of alleles) exceeds the value provided by this argument, then output of all of the PL values will be suppressed.

int  100  [ [ -∞  ∞ ] ]


--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  [ [ -∞  ∞ ] ]


--maxReadsInMemoryPerSample / -maxReadsInMemoryPerSample

Maximum reads per sample given to traversal map() function
What is the maximum number of reads we're willing to hold in memory per sample during the traversal? This limits our exposure to unusually large amounts of coverage in the engine.

int  30000  [ [ -∞  ∞ ] ]


--maxReadsInRegionPerSample / -maxReadsInRegionPerSample

Maximum reads in an active region
When downsampling, level the coverage of the reads in each sample to no more than maxReadsInRegionPerSample reads, not reducing coverage at any read start to less than minReadsPerAlignmentStart

int  1000  [ [ -∞  ∞ ] ]


--maxTotalReadsInMemory / -maxTotalReadsInMemory

Maximum total reads given to traversal map() function
What is the maximum number of reads we're willing to hold in memory per sample during the traversal? This limits our exposure to unusually large amounts of coverage in the engine.

int  10000000  [ [ -∞  ∞ ] ]


--min_base_quality_score / -mbq

Minimum base quality required to consider a base for calling

byte  10  [ [ -∞  ∞ ] ]


--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  [ [ -∞  ∞ ] ]


--minReadsPerAlignmentStart / -minReadsPerAlignStart

Minimum number of reads sharing the same alignment start for each genomic location in an active region

int  5  [ [ -∞  ∞ ] ]


--normal_lod / NA

LOD threshold for calling normal 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.

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.

This argument supports reference-ordered data (ROD) files in the following formats: BCF2, VCF, VCF3

List[RodBinding[VariantContext]]  []


--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  [ [ -∞  ∞ ] ]


--out / -o

File to which variants should be written

VariantContextWriter  stdout


--output_mode / -out_mode

Which type of calls we should output
Experimental argument FOR USE WITH UnifiedGenotyper ONLY. When using HaplotypeCaller, use -ERC instead. When using GenotypeGVCFs, see -allSites.

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


--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  [ [ -∞  ∞ ] ]


--pir_mad_threshold / NA

threshold for clustered read position artifact MAD
This argument is used for the M1-style read position filter

double  3.0  [ [ -∞  ∞ ] ]


--pir_median_threshold / NA

threshold for clustered read position artifact median
This argument is used for the M1-style read position filter

double  10.0  [ [ -∞  ∞ ] ]


--power_constant_qscore / NA

Phred scale quality score constant to use in power calculations
This argument is used for the M1-style strand bias filter

int  30  [ [ -∞  ∞ ] ]


--sample_ploidy / -ploidy

Ploidy per sample. For pooled data, set to (Number of samples in each pool * Sample Ploidy).
Sample ploidy - equivalent to number of chromosome copies per pool. For pooled experiments this should be set to the number of samples in pool multiplied by individual sample ploidy.

int  2  [ [ -∞  ∞ ] ]


--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 Qscore threshold to separate high confidence from low confidence calls. Only genotypes with confidence >= this threshold are emitted as called sites. A reasonable threshold is 30 for high-pass calling (this is the default).

double  10.0  [ [ -∞  ∞ ] ]


--tumor_lod / NA

LOD threshold for calling tumor variant
Only variants with tumor LODs exceeding this threshold can pass filtering.

double  6.3  [ [ -∞  ∞ ] ]


--useFilteredReadsForAnnotations / -useFilteredReadsForAnnotations

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

boolean  false


--useNewAFCalculator / -newQual

Use new AF model instead of the so-called exact model
This activates a model for calculating QUAL that was introduced in version 3.7 (November 2016). We expect this model will become the default in future versions.

boolean  false


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GATK version 3.7-0-gcfedb67 built at 2017/02/09 12:35:06.