Takes unaligned or aligned reads and runs BWA (if specified), MarkDuplicates, BQSR, and HaplotypeCaller to generate a VCF file of variants

Category Short Variant Discovery

---

Overview

ReadsPipelineSpark is our standard pipeline that takes unaligned or aligned reads and runs BWA (if specified), MarkDuplicates, BQSR, and HaplotypeCaller. The final result is analysis-ready variants.

Examples

 gatk ReadsPipelineSpark \
   -I gs://my-gcs-bucket/aligned_reads.bam \
   -R gs://my-gcs-bucket/reference.fasta \
   --known-sites gs://my-gcs-bucket/sites_of_variation.vcf \
   -O gs://my-gcs-bucket/output.vcf \
   -- \
   --sparkRunner GCS \
   --cluster my-dataproc-cluster
 

To additionally align reads with BWA-MEM:

 gatk ReadsPipelineSpark \
   -I gs://my-gcs-bucket/unaligned_reads.bam \
   -R gs://my-gcs-bucket/reference.fasta \
   --known-sites gs://my-gcs-bucket/sites_of_variation.vcf \
   -align
   -O gs://my-gcs-bucket/output.vcf \
   -- \
   --sparkRunner GCS \
   --cluster my-dataproc-cluster
 

ReadsPipelineSpark 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
--known-sites	[]	the known variants
--output  -O	null	the output vcf
--reference  -R	null	Reference sequence file
Optional Tool Arguments
--align	false	whether to perform alignment using BWA-MEM
--alleles	null	The set of alleles at which to genotype when --genotyping_mode is GENOTYPE_GIVEN_ALLELES
--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	[StandardAnnotation, StandardHCAnnotation]	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-padding	100	Number of additional bases of context to include around each assembly region
--bam-partition-size	0	maximum number of bytes to read from a file into each partition of reads. Setting this higher will result in fewer partitions. Note that this will not be equal to the size of the partition in memory. Defaults to 0, which uses the default split size (determined by the Hadoop input format, typically the size of one HDFS block).
--base-quality-score-threshold	18	Base qualities below this threshold will be reduced to the minimum (6)
--binary-tag-name	null	the binary tag covariate name if using it
--bqsr-baq-gap-open-penalty	40.0	BQSR BAQ gap open penalty (Phred Scaled). Default value is 40. 30 is perhaps better for whole genome call sets
--bwa-mem-index-image  -image	null	The BWA-MEM index image file name that you've distributed to each executor
--conf	[]	spark properties to set on the spark context in the format =
--contamination-fraction-to-filter  -contamination	0.0	Fraction of contamination in sequencing data (for all samples) to aggressively remove
--dbsnp  -D	null	dbSNP file
--default-base-qualities	-1	Assign a default base quality
--deletions-default-quality	45	default quality for the base deletions covariate
--disable-sequence-dictionary-validation	false	If specified, do not check the sequence dictionaries from our inputs for compatibility. Use at your own risk!
--duplicates-scoring-strategy  -DS	SUM_OF_BASE_QUALITIES	The scoring strategy for choosing the non-duplicate among candidates.
--emit-original-quals	false	Emit original base qualities under the OQ tag
--gcs-max-retries  -gcs-retries	20	If the GCS bucket channel errors out, how many times it will attempt to re-initiate the connection
--genotyping-mode	DISCOVERY	Specifies how to determine the alternate alleles to use for genotyping
--global-qscore-prior	-1.0	Global Qscore Bayesian prior to use for BQSR
--graph-output  -graph	null	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 eterozygosity 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
--indels-context-size  -ics	3	Size of the k-mer context to be used for base insertions and deletions
--insertions-default-quality	45	default quality for the base insertions covariate
--interval-merging-rule  -imr	ALL	Interval merging rule for abutting intervals
--intervals  -L	[]	One or more genomic intervals over which to operate
--join-strategy	BROADCAST	the join strategy for reference bases and known variants
--low-quality-tail	2	minimum quality for the bases in the tail of the reads to be considered
--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.
--maximum-cycle-value  -max-cycle	500	The maximum cycle value permitted for the Cycle covariate
--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
--mismatches-context-size  -mcs	2	Size of the k-mer context to be used for base mismatches
--mismatches-default-quality	-1	default quality for the base mismatches covariate
--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-reducers	0	For tools that shuffle data or write an output, sets the number of reducers. Defaults to 0, which gives one partition per 10MB of input.
--output-bam	null	the output bam
--output-mode	EMIT_VARIANTS_ONLY	Specifies which type of calls we should output
--preserve-qscores-less-than	6	Don't recalibrate bases with quality scores less than this threshold (with -bqsr)
--program-name	null	Name of the program running
--quantize-quals	0	Quantize quality scores to a given number of levels
--quantizing-levels	16	number of distinct quality scores in the quantized output
--read-shard-padding	100	Each read shard has this many bases of extra context on each side. Read shards must have as much or more padding than assembly regions.
--read-shard-size	5000	Maximum size of each read shard, in bases. For good performance, this should be much larger than the maximum assembly region size.
--sample-name  -ALIAS	null	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).
--sharded-output	false	For tools that write an output, write the output in multiple pieces (shards)
--single-end-alignment  -se	false	Run single-end instead of paired-end alignment
--spark-master	local[*]	URL of the Spark Master to submit jobs to when using the Spark pipeline runner.
--standard-min-confidence-threshold-for-calling  -stand-call-conf	10.0	The minimum phred-scaled confidence threshold at which variants should be called
--use-new-qual-calculator  -new-qual	false	If provided, we will use the new AF model instead of the so-called exact model
--use-original-qualities  -OQ	false	Use the base quality scores from the OQ tag
--version	false	display the version number for this tool
Optional Common Arguments
--disable-read-filter  -DF	[]	Read filters to be disabled before analysis
--disable-tool-default-read-filters	false	Disable all tool default read filters
--exclude-intervals  -XL	[]	One or more genomic intervals to exclude from processing
--gatk-config-file	null	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
--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.
--TMP_DIR	[]	Undocumented option
--use-jdk-deflater  -jdk-deflater	false	Whether to use the JdkDeflater (as opposed to IntelDeflater)
--use-jdk-inflater  -jdk-inflater	false	Whether to use the JdkInflater (as opposed to IntelInflater)
--verbosity	INFO	Control verbosity of logging.
Advanced Arguments
--active-probability-threshold	0.002	Minimum probability for a locus to be considered active.
--all-site-pls	false	Annotate all sites with PLs
--allow-non-unique-kmers-in-ref	false	Allow graphs that have non-unique kmers in the reference
--bam-output  -bamout	null	File to which assembled haplotypes should be written
--bam-writer-type	CALLED_HAPLOTYPES	Which haplotypes should be written to the BAM
--comp	[]	Comparison VCF file(s)
--consensus	false	1000G consensus mode
--contamination-fraction-per-sample-file  -contamination-file	null	Tab-separated File containing fraction of contamination in sequencing data (per sample) to aggressively remove. Format should be "" (Contamination is double) per line; No header.
--debug	false	Print out very verbose debug information about each triggering active region
--disable-optimizations	false	Don't skip calculations in ActiveRegions with no variants
--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-trim-active-regions	false	If specified, we will not trim down the active region from the full region (active + extension) to just the active interval for genotyping
--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
--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
--input-prior	[]	Input prior for calls
--kmer-size	[10, 25]	Kmer size to use in the read threading assembler
--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-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
--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
--pcr-indel-model	CONSERVATIVE	The PCR indel model to use
--phred-scaled-global-read-mismapping-rate	45	The global assumed mismapping rate for reads
--round-down-quantized	false	Round quals down to nearest quantized qual
--showHidden	false	display hidden arguments
--smith-waterman	JAVA	Which Smith-Waterman implementation to use, generally FASTEST_AVAILABLE is the right choice
--static-quantized-quals	[]	Use static quantized quality scores to a given number of levels (with -bqsr)
--use-alleles-trigger	false	Use additional trigger on variants found in an external alleles file
--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 / NA

Minimum probability for a locus to be considered active.

double  0.002  [ [ -∞  ∞ ] ]

---

--align / NA

whether to perform alignment using BWA-MEM

boolean  false

---

--all-site-pls / NA

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

boolean  false

---

--alleles / NA

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

FeatureInput[VariantContext]  null

---

--allow-non-unique-kmers-in-ref / NA

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 / NA

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]  [StandardAnnotation, StandardHCAnnotation]

---

--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 / NA

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

List[File]  []

---

--assembly-region-padding / NA

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

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-partition-size / NA

maximum number of bytes to read from a file into each partition of reads. Setting this higher will result in fewer partitions. Note that this will not be equal to the size of the partition in memory. Defaults to 0, which uses the default split size (determined by the Hadoop input format, typically the size of one HDFS block).

long  0  [ [ -∞  ∞ ] ]

---

--bam-writer-type / NA

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 / NA

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  [ [ -∞  ∞ ] ]

---

--binary-tag-name / NA

the binary tag covariate name if using it
The tag name for the binary tag covariate (if using it)

String  null

---

--bqsr-baq-gap-open-penalty / NA

BQSR BAQ gap open penalty (Phred Scaled). Default value is 40. 30 is perhaps better for whole genome call sets

double  40.0  [ [ -∞  ∞ ] ]

---

--bwa-mem-index-image / -image

The BWA-MEM index image file name that you've distributed to each executor
The BWA-MEM index image file name that you've distributed to each executor. The image file can be generated using {@link BwaMemIndexImageCreator}. If this argument is not specified, the default behavior is to look for a file whose name is the FASTA reference file with a .img suffix.

String  null

---

--comp / -comp

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

List[FeatureInput[VariantContext]]  []

---

--conf / -conf

spark properties to set on the spark context in the format =

List[String]  []

---

--consensus / NA

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 / -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  [ [ -∞  ∞ ] ]

---

--dbsnp / -D

dbSNP file
A dbSNP VCF file.

FeatureInput[VariantContext]  null

---

--debug / -debug

Print out very verbose debug information about each triggering active region

boolean  false

---

--default-base-qualities / NA

Assign a default base quality
If reads are missing some or all base quality scores, this value will be used for all base quality scores. By default this is set to -1 to disable default base quality assignment.

byte  -1  [ [ -∞  ∞ ] ]

---

--deletions-default-quality / NA

default quality for the base deletions covariate
A default base qualities to use as a prior (reported quality) in the mismatch covariate model. This value will replace all base qualities in the read for this default value. Negative value turns it off. [default is on]

byte  45  [ [ -∞  ∞ ] ]

---

--disable-optimizations / NA

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

boolean  false

---

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

Disable all tool default read filters

boolean  false

---

--do-not-run-physical-phasing / NA

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 / NA

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-trim-active-regions / NA

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

---

--dont-use-soft-clipped-bases / NA

Do not analyze soft clipped bases in the reads

boolean  false

---

--duplicates-scoring-strategy / -DS

The scoring strategy for choosing the non-duplicate among candidates.

The --duplicates-scoring-strategy argument is an enumerated type (MarkDuplicatesScoringStrategy), which can have one of the following values:

SUM_OF_BASE_QUALITIES

TOTAL_MAPPED_REFERENCE_LENGTH

MarkDuplicatesScoringStrategy  SUM_OF_BASE_QUALITIES

---

--emit-original-quals / NA

Emit original base qualities under the OQ tag
The tool is capable of writing out the original quality scores of each read in the recalibrated output file under the "OQ" tag. By default, this behavior is disabled because emitting original qualities results in a significant increase of the file size. Use this flag to turn on emission of original qualities.

boolean  false

---

--emit-ref-confidence / -ERC

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

The --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

---

--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]  []

---

--gatk-config-file / NA

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  [ [ -∞  ∞ ] ]

---

--genotyping-mode / NA

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

---

--global-qscore-prior / NA

Global Qscore Bayesian prior to use for BQSR
If specified, the value of this argument will be used as a flat prior for all mismatching quality scores instead of the reported quality score (assigned by the sequencer).

double  -1.0  [ [ -∞  ∞ ] ]

---

--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 / NA

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 / NA

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 / NA

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 / NA

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  [ [ -∞  ∞ ] ]

---

--indels-context-size / -ics

Size of the k-mer context to be used for base insertions and deletions
The context covariate will use a context of this size to calculate its covariate value for base insertions and deletions. Must be between 1 and 13 (inclusive). Note that higher values will increase runtime and required java heap size.

int  3  [ [ -∞  ∞ ] ]

---

--input / -I

BAM/SAM/CRAM file containing reads

R List[String]  []

---

--input-prior / NA

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

List[Double]  []

---

--insertions-default-quality / NA

default quality for the base insertions covariate
A default base qualities to use as a prior (reported quality) in the insertion covariate model. This parameter is used for all reads without insertion quality scores for each base. [default is on]

byte  45  [ [ -∞  ∞ ] ]

---

--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]  []

---

--join-strategy / NA

the join strategy for reference bases and known variants

The --join-strategy argument is an enumerated type (JoinStrategy), which can have one of the following values:

BROADCAST

Use a broadcast join strategy, where one side of the join is collected into memory and broadcast to all workers.

OVERLAPS_PARTITIONER

Use an overlaps partitioner strategy, where one side of the join is sharded in partitions and the other side is broadcast.

SHUFFLE

Use a shuffle join strategy, where both sides of join are shuffled across the workers.

JoinStrategy  BROADCAST

---

--kmer-size / NA

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]

---

--known-sites / NA

the known variants

R List[String]  []

---

--low-quality-tail / NA

minimum quality for the bases in the tail of the reads to be considered
Reads with low quality bases on either tail (beginning or end) will not be considered in the context. This parameter defines the quality below which (inclusive) a tail is considered low quality

byte  2  [ [ -∞  ∞ ] ]

---

--max-alternate-alleles / NA

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 / NA

Maximum size of an assembly region

int  300  [ [ -∞  ∞ ] ]

---

--max-genotype-count / NA

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-num-haplotypes-in-population / NA

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 / NA

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 / NA

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

int  50  [ [ -∞  ∞ ] ]

---

--maximum-cycle-value / -max-cycle

The maximum cycle value permitted for the Cycle covariate
The cycle covariate will generate an error if it encounters a cycle greater than this value. This argument is ignored if the Cycle covariate is not used.

int  500  [ [ -∞  ∞ ] ]

---

--min-assembly-region-size / NA

Minimum size of an assembly region

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 / NA

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 / NA

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  [ [ -∞  ∞ ] ]

---

--mismatches-context-size / -mcs

Size of the k-mer context to be used for base mismatches
The context covariate will use a context of this size to calculate its covariate value for base mismatches. Must be between 1 and 13 (inclusive). Note that higher values will increase runtime and required java heap size.

int  2  [ [ -∞  ∞ ] ]

---

--mismatches-default-quality / NA

default quality for the base mismatches covariate
A default base qualities to use as a prior (reported quality) in the mismatch covariate model. This value will replace all base qualities in the read for this default value. Negative value turns it off. [default is off]

byte  -1  [ [ -∞  ∞ ] ]

---

--native-pair-hmm-threads / NA

How many threads should a native pairHMM implementation use

int  4  [ [ -∞  ∞ ] ]

---

--native-pair-hmm-use-double-precision / NA

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

boolean  false

---

--num-pruning-samples / NA

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-reducers / NA

For tools that shuffle data or write an output, sets the number of reducers. Defaults to 0, which gives one partition per 10MB of input.

int  0  [ [ -∞  ∞ ] ]

---

--output / -O

the output vcf

R String  null

---

--output-bam / NA

the output bam

String  null

---

--output-mode / NA

Specifies which type of calls we should output

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

EMIT_VARIANTS_ONLY

produces calls only at variant sites

EMIT_ALL_CONFIDENT_SITES

produces calls at variant sites and confident reference sites

EMIT_ALL_SITES

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

OutputMode  EMIT_VARIANTS_ONLY

---

--pair-hmm-gap-continuation-penalty / NA

Flat gap continuation penalty for use in the Pair HMM

int  10  [ [ -∞  ∞ ] ]

---

--pcr-indel-model / NA

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

---

--phred-scaled-global-read-mismapping-rate / NA

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  [ [ -∞  ∞ ] ]

---

--preserve-qscores-less-than / NA

Don't recalibrate bases with quality scores less than this threshold (with -bqsr)
This flag tells GATK not to modify quality scores less than this value. Instead they will be written out unmodified in the recalibrated BAM file. In general it's unsafe to change qualities scores below < 6, since base callers use these values to indicate random or bad bases. For example, Illumina writes Q2 bases when the machine has really gone wrong. This would be fine in and of itself, but when you select a subset of these reads based on their ability to align to the reference and their dinucleotide effect, your Q2 bin can be elevated to Q8 or Q10, leading to issues downstream.

int  6  [ [ -∞  ∞ ] ]

---

--program-name / NA

Name of the program running

String  null

---

--quantize-quals / NA

Quantize quality scores to a given number of levels
Turns on the base quantization module. It requires a recalibration report. A value of 0 here means "do not quantize". Any value greater than zero will be used to recalculate the quantization using that many levels. Negative values mean that we should quantize using the recalibration report's quantization level.

Exclusion: This argument cannot be used at the same time as static-quantized-quals, round-down-quantized.

int  0  [ [ -∞  ∞ ] ]

---

--quantizing-levels / NA

number of distinct quality scores in the quantized output
BQSR generates a quantization table for quick quantization later by subsequent tools. BQSR does not quantize the base qualities, this is done by the engine with the -qq or -bqsr options. This parameter tells BQSR the number of levels of quantization to use to build the quantization table.

int  16  [ [ -∞  ∞ ] ]

---

--QUIET / NA

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[String]  []

---

--read-shard-padding / NA

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

int  100  [ [ -∞  ∞ ] ]

---

--read-shard-size / NA

Maximum size of each read shard, in bases. For good performance, this should be much larger than the maximum assembly region size.

int  5000  [ [ -∞  ∞ ] ]

---

--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-dangling-heads / NA

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

boolean  false

---

--reference / -R

Reference sequence file

R String  null

---

--round-down-quantized / NA

Round quals down to nearest quantized qual
Round down quantized only works with the static_quantized_quals option, and should not be used with the dynamic binning option provided by quantize_quals. When roundDown = false, rounding is done in probability space to the nearest bin. When roundDown = true, the value is rounded to the nearest bin that is smaller than the current bin.

Exclusion: This argument cannot be used at the same time as quantize-quals.

boolean  false

---

--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  [ [ -∞  ∞ ] ]

---

--sharded-output / NA

For tools that write an output, write the output in multiple pieces (shards)

boolean  false

---

--showHidden / -showHidden

display hidden arguments

boolean  false

---

--single-end-alignment / -se

Run single-end instead of paired-end alignment
Run single-end instead of paired-end alignment.

boolean  false

---

--smith-waterman / NA

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

---

--spark-master / NA

URL of the Spark Master to submit jobs to when using the Spark pipeline runner.

String  local[*]

---

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

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

double  10.0  [ [ -∞  ∞ ] ]

---

--static-quantized-quals / NA

Use static quantized quality scores to a given number of levels (with -bqsr)
Static quantized quals are entirely separate from the quantize_qual option which uses dynamic binning. The two types of binning should not be used together.

Exclusion: This argument cannot be used at the same time as quantize-quals.

List[Integer]  []

---

--TMP_DIR / NA

Undocumented option

List[File]  []

---

--use-alleles-trigger / NA

Use additional trigger on variants found in an external alleles file

boolean  false

---

--use-filtered-reads-for-annotations / NA

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

---

--use-new-qual-calculator / -new-qual

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

boolean  false

---

--use-original-qualities / -OQ

Use the base quality scores from the OQ tag
This flag tells GATK to use the original base qualities (that were in the data before BQSR/recalibration) which are stored in the OQ tag, if they are present, rather than use the post-recalibration quality scores. If no OQ tag is present for a read, the standard qual score will be used.

Boolean  false

---

--verbosity / -verbosity

Control verbosity of logging.

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

ERROR

WARNING

INFO

DEBUG

LogLevel  INFO

---

--version / NA

display the version number for this tool

boolean  false

---

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GATK version 4.0.0.0 built at 27-36-2019 11:36:13.