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CollectHsMetrics (Picard)

Collects hybrid-selection (HS) metrics for a SAM or BAM file.

This tool takes a SAM/BAM file input and collects metrics that are specific for sequence datasets generated through hybrid-selection. Hybrid-selection (HS) is the most commonly used technique to capture exon-specific sequences for targeted sequencing experiments such as exome sequencing; for more information, please see the corresponding GATK Dictionary entry.

This tool requires an aligned SAM or BAM file as well as bait and target interval files in Picard interval_list format. You should use the bait and interval files that correspond to the capture kit that was used to generate the capture libraries for sequencing, which can generally be obtained from the kit manufacturer. If the baits and target intervals are provided in BED format, you can convert them to the Picard interval_list format using Picard's BedToInterval tool.

If a reference sequence is provided, this program will calculate both AT_DROPOUT and GC_DROPOUT metrics. Dropout metrics are an attempt to measure the reduced representation of reads, in regions that deviate from 50% G/C content. This reduction in the number of aligned reads is due to the increased numbers of errors associated with sequencing regions with excessive or deficient numbers of G/C bases, ultimately leading to poor mapping efficiencies and lowcoverage in the affected regions.

If you are interested in getting G/C content and mean sequence depth information for every target interval, use the PER_TARGET_COVERAGE option.

Note: Metrics labeled as percentages are actually expressed as fractions!

Usage Example:

java -jar picard.jar CollectHsMetrics \
I=input_reads.bam \
O=output_hs_metrics.txt \
R=reference.fasta \
BAIT_INTERVALS=bait.interval_list \
TARGET_INTERVALS=target.interval_list

Please see CollectHsMetrics for detailed descriptions of the output metrics produced by this tool.


Category Diagnostics and Quality Control


Overview

This tool takes a SAM/BAM file input and collects metrics that are specific for sequence datasets generated through hybrid-selection. Hybrid-selection (HS) is the most commonly used technique to capture exon-specific sequences for targeted sequencing experiments such as exome sequencing; for more information, please see the corresponding GATK Dictionary entry.

This tool requires an aligned SAM or BAM file as well as bait and target interval files in Picard interval_list format. You should use the bait and interval files that correspond to the capture kit that was used to generate the capture libraries for sequencing, which can generally be obtained from the kit manufacturer. If the baits and target intervals are provided in BED format, you can convert them to the Picard interval_list format using Picard's BedToInterval tool.

If a reference sequence is provided, this program will calculate both AT_DROPOUT and GC_DROPOUT metrics. Dropout metrics are an attempt to measure the reduced representation of reads, in regions that deviate from 50% G/C content. This reduction in the number of aligned reads is due to the increased numbers of errors associated with sequencing regions with excessive or deficient numbers of G/C bases, ultimately leading to poor mapping efficiencies and low coverage in the affected regions.

If you are interested in getting G/C content and mean sequence depth information for every target interval, use the PER_TARGET_COVERAGE option.

Note: Metrics labeled as percentages are actually expressed as fractions!

Usage Example:

 java -jar picard.jar CollectHsMetrics \\
I=input_reds.bam \\
O=output_hs_metrics.txt \\
" R=reference.fasta \\
BAIT_INTERVALS=bait.interval_list \\
TARGET_INTERVALS=target.interval_list

Please see CollectHsMetrics for detailed descriptions of the output metrics produced by this tool.


See HsMetricCollector and CollectTargetedMetrics for more details.

CollectHsMetrics (Picard) 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
--BAIT_INTERVALS
 -BI
[] An interval list file that contains the locations of the baits used.
--INPUT
 -I
null An aligned SAM or BAM file.
--OUTPUT
 -O
null The output file to write the metrics to.
--TARGET_INTERVALS
 -TI
[] An interval list file that contains the locations of the targets.
Optional Tool Arguments
--ALLELE_FRACTION
[0.001, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.3, 0.5] Allele fraction for which to calculate theoretical sensitivity.
--arguments_file
[] read one or more arguments files and add them to the command line
--BAIT_SET_NAME
 -N
null Bait set name. If not provided it is inferred from the filename of the bait intervals.
--CLIP_OVERLAPPING_READS
true True if we are to clip overlapping reads, false otherwise.
--COVERAGE_CAP
 -covMax
200 Parameter to set a max coverage limit for Theoretical Sensitivity calculations. Default is 200.
--help
 -h
false display the help message
--METRIC_ACCUMULATION_LEVEL
 -LEVEL
[ALL_READS] The level(s) at which to accumulate metrics.
--MINIMUM_BASE_QUALITY
 -Q
20 Minimum base quality for a base to contribute coverage.
--MINIMUM_MAPPING_QUALITY
 -MQ
20 Minimum mapping quality for a read to contribute coverage.
--NEAR_DISTANCE
250 The maximum distance between a read and the nearest probe/bait/amplicon for the read to be considered 'near probe' and included in percent selected.
--PER_BASE_COVERAGE
null An optional file to output per base coverage information to. The per-base file contains one line per target base and can grow very large. It is not recommended for use with large target sets.
--PER_TARGET_COVERAGE
null An optional file to output per target coverage information to.
--SAMPLE_SIZE
10000 Sample Size used for Theoretical Het Sensitivity sampling. Default is 10000.
--THEORETICAL_SENSITIVITY_OUTPUT
null Output for Theoretical Sensitivity metrics where the allele fractions are provided by the ALLELE_FRACTION argument.
--version
false display the version number for this tool
Optional Common Arguments
--COMPRESSION_LEVEL
5 Compression level for all compressed files created (e.g. BAM and VCF).
--CREATE_INDEX
false Whether to create a BAM index when writing a coordinate-sorted BAM file.
--CREATE_MD5_FILE
false Whether to create an MD5 digest for any BAM or FASTQ files created.
--GA4GH_CLIENT_SECRETS
client_secrets.json Google Genomics API client_secrets.json file path.
--MAX_RECORDS_IN_RAM
500000 When writing files that need to be sorted, this will specify the number of records stored in RAM before spilling to disk. Increasing this number reduces the number of file handles needed to sort the file, and increases the amount of RAM needed.
--QUIET
false Whether to suppress job-summary info on System.err.
--REFERENCE_SEQUENCE
 -R
null Reference sequence file.
--TMP_DIR
[] One or more directories with space available to be used by this program for temporary storage of working files
--USE_JDK_DEFLATER
 -use_jdk_deflater
false Use the JDK Deflater instead of the Intel Deflater for writing compressed output
--USE_JDK_INFLATER
 -use_jdk_inflater
false Use the JDK Inflater instead of the Intel Inflater for reading compressed input
--VALIDATION_STRINGENCY
STRICT Validation stringency for all SAM files read by this program. Setting stringency to SILENT can improve performance when processing a BAM file in which variable-length data (read, qualities, tags) do not otherwise need to be decoded.
--VERBOSITY
INFO Control verbosity of logging.
Advanced Arguments
--showHidden
false display hidden arguments

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.


--ALLELE_FRACTION / NA

Allele fraction for which to calculate theoretical sensitivity.

List[Double]  [0.001, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.3, 0.5]


--arguments_file / NA

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

List[File]  []


--BAIT_INTERVALS / -BI

An interval list file that contains the locations of the baits used.

R List[File]  []


--BAIT_SET_NAME / -N

Bait set name. If not provided it is inferred from the filename of the bait intervals.

String  null


--CLIP_OVERLAPPING_READS / NA

True if we are to clip overlapping reads, false otherwise.

boolean  true


--COMPRESSION_LEVEL / NA

Compression level for all compressed files created (e.g. BAM and VCF).

int  5  [ [ -∞  ∞ ] ]


--COVERAGE_CAP / -covMax

Parameter to set a max coverage limit for Theoretical Sensitivity calculations. Default is 200.

int  200  [ [ -∞  ∞ ] ]


--CREATE_INDEX / NA

Whether to create a BAM index when writing a coordinate-sorted BAM file.

Boolean  false


--CREATE_MD5_FILE / NA

Whether to create an MD5 digest for any BAM or FASTQ files created.

boolean  false


--GA4GH_CLIENT_SECRETS / NA

Google Genomics API client_secrets.json file path.

String  client_secrets.json


--help / -h

display the help message

boolean  false


--INPUT / -I

An aligned SAM or BAM file.

R File  null


--MAX_RECORDS_IN_RAM / NA

When writing files that need to be sorted, this will specify the number of records stored in RAM before spilling to disk. Increasing this number reduces the number of file handles needed to sort the file, and increases the amount of RAM needed.

Integer  500000  [ [ -∞  ∞ ] ]


--METRIC_ACCUMULATION_LEVEL / -LEVEL

The level(s) at which to accumulate metrics.

Set[MetricAccumulationLevel]  [ALL_READS]


--MINIMUM_BASE_QUALITY / -Q

Minimum base quality for a base to contribute coverage.

int  20  [ [ -∞  ∞ ] ]


--MINIMUM_MAPPING_QUALITY / -MQ

Minimum mapping quality for a read to contribute coverage.

int  20  [ [ -∞  ∞ ] ]


--NEAR_DISTANCE / NA

The maximum distance between a read and the nearest probe/bait/amplicon for the read to be considered 'near probe' and included in percent selected.

int  250  [ [ -∞  ∞ ] ]


--OUTPUT / -O

The output file to write the metrics to.

R File  null


--PER_BASE_COVERAGE / NA

An optional file to output per base coverage information to. The per-base file contains one line per target base and can grow very large. It is not recommended for use with large target sets.

File  null


--PER_TARGET_COVERAGE / NA

An optional file to output per target coverage information to.

File  null


--QUIET / NA

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

Boolean  false


--REFERENCE_SEQUENCE / -R

Reference sequence file.

File  null


--SAMPLE_SIZE / NA

Sample Size used for Theoretical Het Sensitivity sampling. Default is 10000.

int  10000  [ [ -∞  ∞ ] ]


--showHidden / -showHidden

display hidden arguments

boolean  false


--TARGET_INTERVALS / -TI

An interval list file that contains the locations of the targets.

R List[File]  []


--THEORETICAL_SENSITIVITY_OUTPUT / NA

Output for Theoretical Sensitivity metrics where the allele fractions are provided by the ALLELE_FRACTION argument.

File  null


--TMP_DIR / NA

One or more directories with space available to be used by this program for temporary storage of working files

List[File]  []


--USE_JDK_DEFLATER / -use_jdk_deflater

Use the JDK Deflater instead of the Intel Deflater for writing compressed output

Boolean  false


--USE_JDK_INFLATER / -use_jdk_inflater

Use the JDK Inflater instead of the Intel Inflater for reading compressed input

Boolean  false


--VALIDATION_STRINGENCY / NA

Validation stringency for all SAM files read by this program. Setting stringency to 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 --VALIDATION_STRINGENCY argument is an enumerated type (ValidationStringency), which can have one of the following values:

STRICT
LENIENT
SILENT

ValidationStringency  STRICT


--VERBOSITY / NA

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 4.0.11.0 built at 23-11-2018 02:11:49.