Summary

Clusters the results from a {@link CrosscheckFingerprints} run according to the LOD score. The resulting metric file can be used to assist diagnosing results from {@link CrosscheckFingerprints}. It clusters the connectivity graph between the different groups. Two groups are connected if they have a LOD score greater than the {@link #LOD_THRESHOLD}.

Details

The results of running {@link CrosscheckFingerprints} can be difficult to analyze, especially when many groups are related (meaning LOD greater than {@link #LOD_THRESHOLD}) in non-transitive manner (A is related to B, B is related to C, but A doesn't seem to be related to C.) {@link ClusterCrosscheckMetrics} clusters the metrics from {@link CrosscheckFingerprints} so that all the groups in a cluster are related to each other either directly, or indirectly (thus A, B and C would end up in one cluster.) Two samples can only be in two different clusters if all the samples from these two clusters do not get high LOD scores when compared to each other.

Example

    java -jar picard.jar ClusterCrosscheckMetrics \
             INPUT=sample.crosscheck_metrics \
             LOD_THRESHOLD=3 \
             OUTPUT=sample.clustered.crosscheck_metrics

The resulting file, consists of the {@link ClusteredCrosscheckMetric} class and contains the original crosscheck metric values, for groups that end-up in the same clusters (regardless of LOD score of each comparison). In addition it notes the {@link ClusteredCrosscheckMetric#CLUSTER} identifier and the size of the cluster (in {@link ClusteredCrosscheckMetric#CLUSTER_SIZE}.) Groups that do not have high LOD scores with any other group (including itself!) will not be included in the metric file. Note that cross-group comparisons are not included in the metric file.

Category Diagnostics and Quality Control

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Overview

Summary

Clusters the results from a CrosscheckFingerprints run according to the LOD score. The resulting metric file can be used to assist diagnosing results from CrosscheckFingerprints. It clusters the connectivity graph between the different groups. Two groups are connected if they have a LOD score greater than the #LOD_THRESHOLD.

Details

The results of running CrosscheckFingerprints can be difficult to analyze, especially when many groups are related (meaning LOD greater than #LOD_THRESHOLD) in non-transitive manner (A is related to B, B is related to C, but A doesn't seem to be related to C.) ClusterCrosscheckMetrics clusters the metrics from CrosscheckFingerprints so that all the groups in a cluster are related to each other either directly, or indirectly (thus A, B and C would end up in one cluster.) Two samples can only be in two different clusters if all the samples from these two clusters do not get high LOD scores when compared to each other.

Example

     java -jar picard.jar ClusterCrosscheckMetrics \
              INPUT=sample.crosscheck_metrics \
              LOD_THRESHOLD=3 \
              OUTPUT=sample.clustered.crosscheck_metrics
 

The resulting file, consists of the ClusteredCrosscheckMetric class and contains the original crosscheck metric values, for groups that end-up in the same clusters (regardless of LOD score of each comparison). In addition it notes the ClusteredCrosscheckMetric#CLUSTER identifier and the size of the cluster (in ClusteredCrosscheckMetric#CLUSTER_SIZE.) Groups that do not have high LOD scores with any other group (including itself!) will not be included in the metric file. Note that cross-group comparisons are not included in the metric file.

ClusterCrosscheckMetrics (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
--INPUT  -I	null	The cross-check metrics file to be clustered.
Optional Tool Arguments
--arguments_file	[]	read one or more arguments files and add them to the command line
--help  -h	false	display the help message
--LOD_THRESHOLD  -LOD	0.0	LOD score to be used as the threshold for clustering.
--OUTPUT  -O	null	Output file to write metrics to. Will write to stdout if null.
--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.

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--arguments_file / NA

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

List[File]  []

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--COMPRESSION_LEVEL / NA

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

int  5  [ [ -∞  ∞ ] ]

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--CREATE_INDEX / NA

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

Boolean  false

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--CREATE_MD5_FILE / NA

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

boolean  false

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--GA4GH_CLIENT_SECRETS / NA

Google Genomics API client_secrets.json file path.

String  client_secrets.json

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--help / -h

display the help message

boolean  false

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--INPUT / -I

The cross-check metrics file to be clustered.

R File  null

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--LOD_THRESHOLD / -LOD

LOD score to be used as the threshold for clustering.

double  0.0  [ [ -∞  ∞ ] ]

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--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  [ [ -∞  ∞ ] ]

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--OUTPUT / -O

Output file to write metrics to. Will write to stdout if null.

File  null

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--QUIET / NA

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

Boolean  false

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--REFERENCE_SEQUENCE / -R

Reference sequence file.

File  null

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--showHidden / -showHidden

display hidden arguments

boolean  false

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--TMP_DIR / NA

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

List[File]  []

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--USE_JDK_DEFLATER / -use_jdk_deflater

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

Boolean  false

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--USE_JDK_INFLATER / -use_jdk_inflater

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

Boolean  false

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--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

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--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

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--version / NA

display the version number for this tool

boolean  false

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GATK version 4.0.1.2 built at 02-02-2019 02:02:55.