HaplotypeCaller – GATK

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

Category Short Variant Discovery

Overview

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

The HaplotypeCaller is capable of calling SNPs and indels simultaneously via local de-novo assembly of haplotypes in an active region. In other words, whenever the program encounters a region showing signs of variation, it discards the existing mapping information and completely reassembles the reads in that region. This allows the HaplotypeCaller to be more accurate when calling regions that are traditionally difficult to call, for example when they contain different types of variants close to each other. It also makes the HaplotypeCaller much better at calling indels than position-based callers like UnifiedGenotyper.

In the GVCF workflow used for scalable variant calling in DNA sequence data, HaplotypeCaller runs per-sample to generate an intermediate GVCF (not to be used in final analysis), which can then be used in GenotypeGVCFs for joint genotyping of multiple samples in a very efficient way. The GVCF workflow enables rapid incremental processing of samples as they roll off the sequencer, as well as scaling to very large cohort sizes (e.g. the 92K exomes of ExAC).

In addition, HaplotypeCaller is able to handle non-diploid organisms as well as pooled experiment data. Note however that the algorithms used to calculate variant likelihoods is not well suited to extreme allele frequencies (relative to ploidy) so its use is not recommended for somatic (cancer) variant discovery. For that purpose, use Mutect2 instead.

Finally, HaplotypeCaller is also able to correctly handle the splice junctions that make RNAseq a challenge for most variant callers, on the condition that the input read data has previously been processed according to our recommendations as documented here.

How HaplotypeCaller works

1. Define active regions

The program determines which regions of the genome it needs to operate on (active regions), based on the presence of evidence for variation.

2. Determine haplotypes by assembly of the active region

For each active region, the program builds a De Bruijn-like graph to reassemble the active region and identifies what are the possible haplotypes present in the data. The program then realigns each haplotype against the reference haplotype using the Smith-Waterman algorithm in order to identify potentially variant sites.

3. Determine likelihoods of the haplotypes given the read data

For each active region, the program performs a pairwise alignment of each read against each haplotype using the PairHMM algorithm. This produces a matrix of likelihoods of haplotypes given the read data. These likelihoods are then marginalized to obtain the likelihoods of alleles for each potentially variant site given the read data.

4. Assign sample genotypes

For each potentially variant site, the program applies Bayes' rule, using the likelihoods of alleles given the read data to calculate the likelihoods of each genotype per sample given the read data observed for that sample. The most likely genotype is then assigned to the sample.

Input

Input bam file(s) from which to make variant calls

Output

Either a VCF or GVCF file with raw, unfiltered SNP and indel calls. Regular VCFs must be filtered either by variant recalibration (Best Practice) or hard-filtering before use in downstream analyses. If using the GVCF workflow, the output is a GVCF file that must first be run through GenotypeGVCFs and then filtering before further analysis.

Usage examples

These are example commands that show how to run HaplotypeCaller for typical use cases. Have a look at the method documentation for the basic GVCF workflow.

Single-sample GVCF calling (outputs intermediate GVCF)

 gatk --java-options "-Xmx4g" HaplotypeCaller  \
   -R Homo_sapiens_assembly38.fasta \
   -I input.bam \
   -O output.g.vcf.gz \
   -ERC GVCF

Single-sample GVCF calling with allele-specific annotations

 gatk --java-options "-Xmx4g" HaplotypeCaller  \
   -R Homo_sapiens_assembly38.fasta \
   -I input.bam \
   -O output.g.vcf.gz \
   -ERC GVCF \
   -G Standard \
   -G AS_Standard

Variant calling with bamout to show realigned reads

 gatk --java-options "-Xmx4g" HaplotypeCaller  \
   -R Homo_sapiens_assembly38.fasta \
   -I input.bam \
   -O output.vcf.gz \
   -bamout bamout.bam

Caveats

We have not yet fully tested the interaction between the GVCF-based calling or the multisample calling and the RNAseq-specific functionalities. Use those in combination at your own risk.

Special note on ploidy

This tool is able to handle many non-diploid use cases; the desired ploidy can be specified using the -ploidy argument. Note however that very high ploidies (such as are encountered in large pooled experiments) may cause performance challenges including excessive slowness. We are working on resolving these limitations.

Additional Notes

When working with PCR-free data, be sure to set `-pcr_indel_model NONE` (see argument below).
When running in `-ERC GVCF` or `-ERC BP_RESOLUTION` modes, the confidence threshold is automatically set to 0. This cannot be overridden by the command line. The threshold can be set manually to the desired level in the next step of the workflow (GenotypeGVCFs)
We recommend using a list of intervals to speed up analysis. See this document for details.

Additional Information

Read filters

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

HaplotypeCaller 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		File to which variants should be written
--reference -R		Reference sequence file
Optional Tool Arguments
--alleles		The set of alleles to force-call regardless of evidence
--annotate-with-num-discovered-alleles	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
--annotation-group -G		One or more groups of annotations to apply to variant calls
--annotations-to-exclude -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
--assembly-region-out		Output the assembly region to this IGV formatted file
--assembly-region-padding	100	Number of additional bases of context to include around each assembly region
--base-quality-score-threshold	18	Base qualities below this threshold will be reduced to the minimum (6)
--cloud-index-prefetch-buffer -CIPB	-1	Size of the cloud-only prefetch buffer (in MB; 0 to disable). Defaults to cloudPrefetchBuffer if unset.
--cloud-prefetch-buffer -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		dbSNP file
--disable-bam-index-caching -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.
--disable-sequence-dictionary-validation	false	If specified, do not check the sequence dictionaries from our inputs for compatibility. Use at your own risk!
--founder-id		Samples representing the population "founders"
--gcs-max-retries -gcs-retries	20	If the GCS bucket channel errors out, how many times it will attempt to re-initiate the connection
--gcs-project-for-requester-pays		Project to bill when accessing "requester pays" buckets. If unset, these buckets cannot be accessed. User must have storage.buckets.get permission on the bucket being accessed.
--graph-output -graph		Write debug assembly graph information to this file
--help -h	false	display the help message
--heterozygosity	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	0.01	Standard deviation of heterozygosity for SNP and indel calling.
--indel-heterozygosity	1.25E-4	Heterozygosity for indel calling. See the GATKDocs for heterozygosity for full details on the meaning of this population genetics concept
--interval-merging-rule -imr	ALL	Interval merging rule for abutting intervals
--intervals -L		One or more genomic intervals over which to operate
--max-assembly-region-size	300	Maximum size of an assembly region
--max-reads-per-alignment-start	50	Maximum number of reads to retain per alignment start position. Reads above this threshold will be downsampled. Set to 0 to disable.
--min-assembly-region-size	50	Minimum size of an assembly region
--min-base-quality-score -mbq	10	Minimum base quality required to consider a base for calling
--native-pair-hmm-threads	4	How many threads should a native pairHMM implementation use
--native-pair-hmm-use-double-precision	false	use double precision in the native pairHmm. This is slower but matches the java implementation better
--num-reference-samples-if-no-call	0	Number of hom-ref genotypes to infer at sites not present in a panel
--output-mode	EMIT_VARIANTS_ONLY	Specifies which type of calls we should output
--pedigree -ped		Pedigree file for determining the population "founders"
--population-callset -population		Callset to use in calculating genotype priors
--sample-name -ALIAS		Name of single sample to use from a multi-sample bam
--sample-ploidy -ploidy	2	Ploidy (number of chromosomes) per sample. For pooled data, set to (Number of samples in each pool * Sample Ploidy).
--sites-only-vcf-output	false	If true, don't emit genotype fields when writing vcf file output.
--standard-min-confidence-threshold-for-calling -stand-call-conf	30.0	The minimum phred-scaled confidence threshold at which variants should be called
--version	false	display the version number for this tool
Optional Common Arguments
--add-output-sam-program-record	true	If true, adds a PG tag to created SAM/BAM/CRAM files.
--add-output-vcf-command-line	true	If true, adds a command line header line to created VCF files.
--create-output-bam-index -OBI	true	If true, create a BAM/CRAM index when writing a coordinate-sorted BAM/CRAM file.
--create-output-bam-md5 -OBM	false	If true, create a MD5 digest for any BAM/SAM/CRAM file created
--create-output-variant-index -OVI	true	If true, create a VCF index when writing a coordinate-sorted VCF file.
--create-output-variant-md5 -OVM	false	If true, create a a MD5 digest any VCF file created.
--disable-read-filter -DF		Read filters to be disabled before analysis
--disable-tool-default-read-filters	false	Disable all tool default read filters (WARNING: many tools will not function correctly without their default read filters on)
--exclude-intervals -XL		One or more genomic intervals to exclude from processing
--gatk-config-file		A configuration file to use with the GATK.
--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.
--read-filter -RF		Read filters to be applied before analysis
--read-index		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.
--read-validation-stringency -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.
--seconds-between-progress-updates	10.0	Output traversal statistics every time this many seconds elapse
--sequence-dictionary		Use the given sequence dictionary as the master/canonical sequence dictionary. Must be a .dict file.
--tmp-dir		Temp directory to use.
--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
--active-probability-threshold	0.002	Minimum probability for a locus to be considered active.
--adaptive-pruning	false	Use Mutect2's adaptive graph pruning algorithm
--adaptive-pruning-initial-error-rate	0.001	Initial base error rate estimate for adaptive pruning
--all-site-pls	false	Annotate all sites with PLs
--allele-informative-reads-overlap-margin	2	Likelihood and read-based annotations will only take into consideration reads that overlap the variant or any base no further than this distance expressed in base pairs
--allow-non-unique-kmers-in-ref	false	Allow graphs that have non-unique kmers in the reference
--bam-output -bamout		File to which assembled haplotypes should be written
--bam-writer-type	CALLED_HAPLOTYPES	Which haplotypes should be written to the BAM
--comparison -comp		Comparison VCF file(s)
--contamination-fraction-per-sample-file -contamination-file		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-assembly -debug	false	Print out verbose debug information about each assembly region
--disable-optimizations	false	Don't skip calculations in ActiveRegions with no variants
--disable-tool-default-annotations	false	Disable all tool default annotations
--do-not-correct-overlapping-quality	false	Disable overlapping base quality correction
--do-not-run-physical-phasing	false	Disable physical phasing
--dont-increase-kmer-sizes-for-cycles	false	Disable iterating over kmer sizes when graph cycles are detected
--dont-use-soft-clipped-bases	false	Do not analyze soft clipped bases in the reads
--emit-ref-confidence -ERC	NONE	Mode for emitting reference confidence scores (For Mutect2, this is a BETA feature)
--enable-all-annotations	false	Use all possible annotations (not for the faint of heart)
--floor-blocks	false	Output the band lower bound for each GQ block regardless of the data it represents
--force-active	false	If provided, all regions will be marked as active
--force-call-filtered-alleles -genotype-filtered-alleles	false	Force-call filtered alleles included in the resource specified by --alleles
--gvcf-gq-bands -GQB	[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 70, 80, 90, 99]	Exclusive upper bounds for reference confidence GQ bands (must be in [1, 100] and specified in increasing order)
--indel-size-to-eliminate-in-ref-model	10	The size of an indel to check for in the reference model
--kmer-size	[10, 25]	Kmer size to use in the read threading assembler
--linked-de-bruijn-graph	false	If enabled, the Assembly Engine will construct a Linked De Bruijn graph to recover better haplotypes
--max-alternate-alleles	6	Maximum number of alternate alleles to genotype
--max-genotype-count	1024	Maximum number of genotypes to consider at any site
--max-mnp-distance -mnp-dist	0	Two or more phased substitutions separated by this distance or less are merged into MNPs.
--max-num-haplotypes-in-population	128	Maximum number of haplotypes to consider for your population
--max-prob-propagation-distance	50	Upper limit on how many bases away probability mass can be moved around when calculating the boundaries between active and inactive assembly regions
--max-unpruned-variants	100	Maximum number of variants in graph the adaptive pruner will allow
--min-dangling-branch-length	4	Minimum length of a dangling branch to attempt recovery
--min-pruning	2	Minimum support to not prune paths in the graph
--num-pruning-samples	1	Number of samples that must pass the minPruning threshold
--pair-hmm-gap-continuation-penalty	10	Flat gap continuation penalty for use in the Pair HMM
--pair-hmm-implementation -pairHMM	FASTEST_AVAILABLE	The PairHMM implementation to use for genotype likelihood calculations
--pcr-indel-model	CONSERVATIVE	The PCR indel model to use
--phred-scaled-global-read-mismapping-rate	45	The global assumed mismapping rate for reads
--pruning-lod-threshold	2.302585092994046	Ln likelihood ratio threshold for adaptive pruning algorithm
--pruning-seeding-lod-threshold	9.210340371976184	Ln likelihood ratio threshold for seeding subgraph of good variation in adaptive pruning algorithm
--recover-all-dangling-branches	false	Recover all dangling branches
--showHidden	false	display hidden arguments
--smith-waterman	JAVA	Which Smith-Waterman implementation to use, generally FASTEST_AVAILABLE is the right choice
--use-filtered-reads-for-annotations	false	Use the contamination-filtered read maps for the purposes of annotating variants
Deprecated Arguments
--recover-dangling-heads	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.

--active-probability-threshold

Minimum probability for a locus to be considered active.

double 0.002 [ [ -∞ ∞ ] ]

--adaptive-pruning

Use Mutect2's adaptive graph pruning algorithm
A single edge multiplicity cutoff for pruning doesn't work in samples with variable depths, for example exomes and RNA. This parameter enables the probabilistic algorithm for pruning the assembly graph that considers the likelihood that each chain in the graph comes from real variation.

boolean false

--adaptive-pruning-initial-error-rate

Initial base error rate estimate for adaptive pruning
Initial base error rate guess for the probabilistic adaptive pruning model. Results are not very sensitive to this parameter because it is only a starting point from which the algorithm discovers the true error rate.

double 0.001 [ [ -∞ ∞ ] ]

--add-output-sam-program-record / -add-output-sam-program-record

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

boolean true

--add-output-vcf-command-line / -add-output-vcf-command-line

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

boolean true

--all-site-pls

Annotate all sites with PLs
Advanced, experimental argument: if SNP likelihood model is specified, and if EMIT_ALL_ACTIVE_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_ACTIVE_SITES is not set, or if anything other than diploid SNP model is used

boolean false

--allele-informative-reads-overlap-margin

Likelihood and read-based annotations will only take into consideration reads that overlap the variant or any base no further than this distance expressed in base pairs

int 2 [ [ -∞ ∞ ] ]

--alleles

The set of alleles to force-call regardless of evidence

FeatureInput[VariantContext] null

--allow-non-unique-kmers-in-ref

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

--annotate-with-num-discovered-alleles

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] []

--annotation-group / -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] []

--annotations-to-exclude / -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

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

List[File] []

--assembly-region-out

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

String null

--assembly-region-padding

Number of additional bases of context to include around each assembly region
Parameters that control assembly regions

int 100 [ [ -∞ ∞ ] ]

--bam-output / -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

--bam-writer-type

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 --bam-writer-type 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

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 [ [ -∞ ∞ ] ]

--cloud-index-prefetch-buffer / -CIPB

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

int -1 [ [ -∞ ∞ ] ]

--cloud-prefetch-buffer / -CPB

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

int 40 [ [ -∞ ∞ ] ]

--comparison / -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]] []

--contamination-fraction-per-sample-file / -contamination-file

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 [ [ -∞ ∞ ] ]

--create-output-bam-index / -OBI

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

boolean true

--create-output-bam-md5 / -OBM

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

boolean false

--create-output-variant-index / -OVI

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

boolean true

--create-output-variant-md5 / -OVM

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

boolean false

--dbsnp / -D

dbSNP file
A dbSNP VCF file.

FeatureInput[VariantContext] null

--debug-assembly / -debug

Print out verbose debug information about each assembly region

boolean false

--disable-bam-index-caching / -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

--disable-optimizations

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 --force-active flag may also be necessary.

boolean false

--disable-read-filter / -DF

Read filters to be disabled before analysis

List[String] []

--disable-sequence-dictionary-validation / -disable-sequence-dictionary-validation

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

boolean false

--disable-tool-default-annotations / -disable-tool-default-annotations

Disable all tool default annotations
Hook allowing for the user to remove default annotations from the tool

boolean false

--disable-tool-default-read-filters / -disable-tool-default-read-filters

Disable all tool default read filters (WARNING: many tools will not function correctly without their default read filters on)

boolean false

--do-not-correct-overlapping-quality

Disable overlapping base quality correction
Base quality is capped at half of PCR error rate for bases where read and mate overlap, to account for full correlation of PCR errors at these bases. This argument disables that correction.

boolean false

--do-not-run-physical-phasing

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

--dont-increase-kmer-sizes-for-cycles

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

--dont-use-soft-clipped-bases

Do not analyze soft clipped bases in the reads

boolean false

--emit-ref-confidence / -ERC

Mode for emitting reference confidence scores (For Mutect2, this is a BETA feature)
The reference confidence mode makes it possible to emit a per-bp or summarized confidence estimate for a site being strictly homozygous-reference. See https://software.broadinstitute.org/gatk/documentation/article.php?id=4017 for information about GVCFs. For Mutect2, this is a BETA feature that functions similarly to the HaplotypeCaller reference confidence/GVCF mode.

The --emit-ref-confidence 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-all-annotations

Use all possible annotations (not for the faint of heart)
You can use the -AX argument in combination with this one to exclude specific annotations. Note that some annotations may not be actually applied if they are not applicable to the data provided or if they are unavailable to the tool (e.g. there are several annotations that are currently not hooked up to HaplotypeCaller). At present no error or warning message will be provided, the annotation will simply be skipped silently. You can check the output VCF header to see which annotations were activated and thus might be applied (although this does not guarantee that the annotation was applied to all records in the VCF, since some annotations have additional requirements, e.g. minimum number of samples or heterozygous sites only -- see the documentation for individual annotations' requirements).

boolean false

--exclude-intervals / -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] []

--floor-blocks

Output the band lower bound for each GQ block regardless of the data it represents
Output the band lower bound for each GQ block instead of the min GQ -- for better compression

boolean false

--force-active

If provided, all regions will be marked as active

boolean false

--force-call-filtered-alleles / -genotype-filtered-alleles

Force-call filtered alleles included in the resource specified by --alleles

boolean false

--founder-id / -founder-id

Samples representing the population "founders"

List[String] []

--gatk-config-file

A configuration file to use with the GATK.

String null

--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 [ [ -∞ ∞ ] ]

--gcs-project-for-requester-pays

Project to bill when accessing "requester pays" buckets. If unset, these buckets cannot be accessed. User must have storage.buckets.get permission on the bucket being accessed.

String ""

--graph-output / -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

--gvcf-gq-bands / -GQB

Exclusive upper bounds for reference confidence GQ bands (must be in [1, 100] and specified in increasing order)
When HC is run in reference confidence mode with banding compression enabled (-ERC GVCF), homozygous-reference sites are compressed into bands of similar genotype quality (GQ) that are emitted as a single VCF record. See the FAQ documentation for more details about the GVCF format. This argument allows you to set the GQ bands. HC expects a list of strictly increasing GQ values that will act as exclusive upper bounds for the GQ bands. To pass multiple values, you provide them one by one with the argument, as in `-GQB 10 -GQB 20 -GQB 30` and so on (this would set the GQ bands to be `[0, 10), [10, 20), [20, 30)` and so on, for example). Note that GQ values are capped at 99 in the GATK, so values must be integers in [1, 100]. If the last value is strictly less than 100, the last GQ band will start at that value (inclusive) and end at 100 (exclusive).

List[Integer] [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 70, 80, 90, 99]

--help / -h

display the help message

boolean false

--heterozygosity

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

Standard deviation of heterozygosity 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

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 [ [ -∞ ∞ ] ]

--indel-size-to-eliminate-in-ref-model

The size of an indel to check for in the reference model
This parameter determines the maximum size of an indel considered as potentially segregating in the reference model. It is used to eliminate reads from being indel informative at a site, and determines by that mechanism the certainty in the reference base. Conceptually, setting this parameter to X means that each informative read is consistent with any indel of size < X being present at a specific position in the genome, given its alignment to the reference.

int 10 [ [ -∞ ∞ ] ]

--input / -I

BAM/SAM/CRAM file containing reads

R List[GATKPath] []

--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] []

--kmer-size

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

List[Integer] [10, 25]

--lenient / -LE

Lenient processing of VCF files

boolean false

--linked-de-bruijn-graph

If enabled, the Assembly Engine will construct a Linked De Bruijn graph to recover better haplotypes
Disables graph simplification into a seq graph, opts to construct a proper De Bruijn graph with potential loops NOTE: --linked-de-bruijn-graph is currently an experimental feature that does not directly match with the regular HaplotypeCaller. Specifically the haplotype finding code does not perform correctly at complicated sites. Use this mode at your own risk.

boolean false

--max-alternate-alleles

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-assembly-region-size

Maximum size of an assembly region

int 300 [ [ -∞ ∞ ] ]

--max-genotype-count

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-mnp-distance / -mnp-dist

Two or more phased substitutions separated by this distance or less are merged into MNPs.
Two or more phased substitutions separated by this distance or less are merged into MNPs.

int 0 [ [ -∞ ∞ ] ]

--max-num-haplotypes-in-population

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 [ [ -∞ ∞ ] ]

--max-prob-propagation-distance

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 [ [ -∞ ∞ ] ]

--max-reads-per-alignment-start

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

int 50 [ [ -∞ ∞ ] ]

--max-unpruned-variants

Maximum number of variants in graph the adaptive pruner will allow
The maximum number of variants in graph the adaptive pruner will allow

int 100 [ [ -∞ ∞ ] ]

--min-assembly-region-size

Minimum size of an assembly region
Parameters that control active regions

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 [ [ -∞ ∞ ] ]

--min-dangling-branch-length

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 [ [ -∞ ∞ ] ]

--min-pruning

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 [ [ -∞ ∞ ] ]

--native-pair-hmm-threads

How many threads should a native pairHMM implementation use

int 4 [ [ -∞ ∞ ] ]

--native-pair-hmm-use-double-precision

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

boolean false

--num-pruning-samples

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 [ [ -∞ ∞ ] ]

--num-reference-samples-if-no-call

Number of hom-ref genotypes to infer at sites not present in a panel
When a variant is not seen in any panel, this argument controls whether to infer (and with what effective strength) that only reference alleles were observed at that site. E.g. "If not seen in 1000Genomes, treat it as AC=0, AN=2000".

int 0 [ [ -∞ ∞ ] ]

--output / -O

File to which variants should be written
A raw, unfiltered, highly sensitive callset in VCF format.

R String null

--output-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_ACTIVE_SITES: Produces calls at any region over the activity threshold regardless of confidence. On occasion, this will output HOM_REF records where no call could be confidently made. This does not necessarily output calls for all sites in a region. This argument is intended only for point mutations (SNPs); it will not produce a comprehensive set of indels.

OutputMode EMIT_VARIANTS_ONLY

--pair-hmm-gap-continuation-penalty

Flat gap continuation penalty for use in the Pair HMM

int 10 [ [ -∞ ∞ ] ]

--pair-hmm-implementation / -pairHMM

The PairHMM implementation to use for genotype likelihood calculations
The PairHMM implementation to use for genotype likelihood calculations. The various implementations balance a tradeoff of accuracy and runtime.

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

EXACT
ORIGINAL
LOGLESS_CACHING
AVX_LOGLESS_CACHING
AVX_LOGLESS_CACHING_OMP
EXPERIMENTAL_FPGA_LOGLESS_CACHING
FASTEST_AVAILABLE

Implementation FASTEST_AVAILABLE

--pcr-indel-model

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

--pedigree / -ped

Pedigree file for determining the population "founders"

File null

--phred-scaled-global-read-mismapping-rate

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 [ [ -∞ ∞ ] ]

--population-callset / -population

Callset to use in calculating genotype priors
Supporting external panel. Allele counts from this panel (taken from AC,AN or MLEAC,AN or raw genotypes) will be used to inform the frequency distribution underlying the genotype priors. These files must be VCF 4.2 spec or later. Note that unlike CalculateGenotypePosteriors, HaplotypeCaller only allows one supporting callset.

FeatureInput[VariantContext] null

--pruning-lod-threshold

Ln likelihood ratio threshold for adaptive pruning algorithm
Log-10 likelihood ratio threshold for adaptive pruning algorithm.

double 2.302585092994046 [ [ -∞ ∞ ] ]

--pruning-seeding-lod-threshold

Ln likelihood ratio threshold for seeding subgraph of good variation in adaptive pruning algorithm
Log-10 likelihood ratio threshold for adaptive pruning algorithm.

double 9.210340371976184 [ [ -∞ ∞ ] ]

--QUIET

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

Boolean false

--read-filter / -RF

Read filters to be applied before analysis

List[String] []

--read-index / -read-index

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[GATKPath] []

--read-validation-stringency / -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 --read-validation-stringency argument is an enumerated type (ValidationStringency), which can have one of the following values:

STRICT
LENIENT
SILENT

ValidationStringency SILENT

--recover-all-dangling-branches

Recover all dangling branches
By default, the read threading assembler does not recover dangling branches that fork after splitting from the reference. This argument tells the assembly engine to recover all dangling branches.

boolean false

--recover-dangling-heads

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 GATKPath null

--sample-name / -ALIAS

Name of single sample to use from a multi-sample bam
You can use this argument to specify that HC should process a single sample out of a multisample BAM file. This is especially useful if your samples are all in the same file but you need to run them individually through HC in -ERC GVC mode (which is the recommended usage). Note that the name is case-sensitive.

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 [ [ -∞ ∞ ] ]

--seconds-between-progress-updates / -seconds-between-progress-updates

Output traversal statistics every time this many seconds elapse

double 10.0 [ [ -∞ ∞ ] ]

--sequence-dictionary / -sequence-dictionary

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

--sites-only-vcf-output

If true, don't emit genotype fields when writing vcf file output.

boolean false

--smith-waterman

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

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

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

Implementation JAVA

--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. Note that the default was changed from 10.0 to 30.0 in version 4.1.0.0 to accompany the switch to use the the new quality score by default.

double 30.0 [ [ -∞ ∞ ] ]

--tmp-dir

Temp directory to use.

GATKPath null

--use-filtered-reads-for-annotations

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

boolean false

--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

--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

display the version number for this tool

boolean false

Return to top

GATK version 4.1.9.0-SNAPSHOT built at Mon, 19 Oct 2020 11:41:12 -0400.

1 comment

David Parry

February 20, 2021 21:51
The "Single-sample GVCF calling with allele-specific annotations" example is out of date. The example annotation groups no longer work in this version of GATK.

The example should read:
```
gatk --java-options "-Xmx4g" HaplotypeCaller  \
   -R Homo_sapiens_assembly38.fasta \
   -I input.bam \
   -O output.g.vcf.gz \
   -ERC GVCF \
   -G StandardAnnotation \
   -G AS_StandardAnnotation
```
0

Comment actions Permalink

Please sign in to leave a comment.

Genome Analysis Toolkit

Need Help?

Community Forum

Articles in this section

Category Short Variant Discovery

Overview

How HaplotypeCaller works

Input

Output

Usage examples

Single-sample GVCF calling (outputs intermediate GVCF)

Single-sample GVCF calling with allele-specific annotations

Variant calling with bamout to show realigned reads

Caveats

Special note on ploidy

Additional Notes

Additional Information

Read filters

HaplotypeCaller specific arguments

Argument details

--add-output-sam-program-record / -add-output-sam-program-record

--add-output-vcf-command-line / -add-output-vcf-command-line

--annotation / -A

--annotation-group / -G

--annotations-to-exclude / -AX

--bam-output / -bamout

--cloud-index-prefetch-buffer / -CIPB

--cloud-prefetch-buffer / -CPB

--comparison / -comp

--contamination-fraction-per-sample-file / -contamination-file

--contamination-fraction-to-filter / -contamination

--create-output-bam-index / -OBI

--create-output-bam-md5 / -OBM

--create-output-variant-index / -OVI

--create-output-variant-md5 / -OVM

--dbsnp / -D

--debug-assembly / -debug

--disable-bam-index-caching / -DBIC

--disable-read-filter / -DF

--disable-sequence-dictionary-validation / -disable-sequence-dictionary-validation

--disable-tool-default-annotations / -disable-tool-default-annotations

--disable-tool-default-read-filters / -disable-tool-default-read-filters

--emit-ref-confidence / -ERC

--exclude-intervals / -XL

--force-call-filtered-alleles / -genotype-filtered-alleles

--founder-id / -founder-id

--gcs-max-retries / -gcs-retries

--graph-output / -graph

--gvcf-gq-bands / -GQB

--help / -h

--input / -I

--interval-exclusion-padding / -ixp

--interval-merging-rule / -imr

--interval-padding / -ip

--interval-set-rule / -isr

--intervals / -L

--lenient / -LE

--max-mnp-distance / -mnp-dist

--min-base-quality-score / -mbq

--output / -O

--pair-hmm-implementation / -pairHMM

--pedigree / -ped

--population-callset / -population

--read-filter / -RF

--read-index / -read-index

--read-validation-stringency / -VS

--reference / -R

--sample-name / -ALIAS

--sample-ploidy / -ploidy

--seconds-between-progress-updates / -seconds-between-progress-updates

--sequence-dictionary / -sequence-dictionary

--showHidden / -showHidden

--standard-min-confidence-threshold-for-calling / -stand-call-conf

--use-jdk-deflater / -jdk-deflater

--use-jdk-inflater / -jdk-inflater

--verbosity / -verbosity

Related articles