Write variant tensors for training a CNN to filter variants

Category Variant Filtering

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Overview

Write variant tensors for training a Convolutional Neural Network (CNN) for filtering variants. After running this tool, a model can be trained with the CNNVariantTrain tool.

Inputs

• The input variants to make into tensors. These variant calls must be annotated with the standard best practices annotations.
• The truth VCF has validated variant calls, like those in the genomes in a bottle, platinum genomes, or CHM VCFs. Variants in both the input VCF and the truth VCF will be used as positive training data.
• The truth BED is a bed file define the confident region for the validated calls. Variants from the input VCF inside this region, but not included in the truth VCF will be used as negative training data.
• The tensor-name argument determines what types of tensors will be written. Set it to "reference" to write 1D tensors or "read_tensor" to write 2D tensors.
• The bam-file argument is necessary to write 2D tensors which incorporate read data.

Outputs

• data-dir This directory is created and populated with variant tensors. it will be divided into training, validation and test sets and each set will be further divided into positive and negative SNPs and INDELs.

Usage example

Write Reference Tensors

 gatk CNNVariantWriteTensors \
   -R reference.fasta \
   -V input.vcf.gz \
   -truth-vcf platinum-genomes.vcf \
   -truth-bed platinum-confident-region.bed \
   -tensor-name reference \
   -output-tensor-dir my-tensor-folder
 

Write Read Tensors

 gatk CNNVariantWriteTensors \
   -R reference.fasta \
   -V input.vcf.gz \
   -truth-vcf platinum-genomes.vcf \
   -truth-bed platinum-confident-region.bed \
   -tensor-name read_tensor \
   -bam-file input.bam \
   -output-tensor-dir my-tensor-folder
 

CNNVariantWriteTensors 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
--output-tensor-dir	null	Directory of training tensors. Subdivided into train, valid and test sets.
--reference  -R	null	Reference fasta file.
--truth-bed	null	Confident region of the validated VCF file.
--truth-vcf	null	Validated VCF file.
--variant  -V	null	Input VCF file
Optional Tool Arguments
--arguments_file	[]	read one or more arguments files and add them to the command line
--bam-file	""	BAM or BAMout file to use for read data when generating 2D tensors.
--gcs-max-retries  -gcs-retries	20	If the GCS bucket channel errors out, how many times it will attempt to re-initiate the connection
--help  -h	false	display the help message
--max-tensors	1000000	Maximum number of tensors to write.
--tensor-type	reference	Name of the tensors to generate.
--version	false	display the version number for this tool
Optional Common Arguments
--gatk-config-file	null	A configuration file to use with the GATK.
--QUIET	false	Whether to suppress job-summary info on System.err.
--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
--annotation-set	best_practices	Which set of annotations to use.
--channels-last	true	Store the channels in the last axis of tensors, tensorflow->true, theano->false
--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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--annotation-set / -annotation-set

Which set of annotations to use.

String  best_practices

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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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--bam-file / -bam-file

BAM or BAMout file to use for read data when generating 2D tensors.

String  ""

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--channels-last / -channels-last

Store the channels in the last axis of tensors, tensorflow->true, theano->false

boolean  true

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--gatk-config-file / NA

A configuration file to use with the GATK.

String  null

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--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  [ [ -∞  ∞ ] ]

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--help / -h

display the help message

boolean  false

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--max-tensors / -max-tensors

Maximum number of tensors to write.

int  1000000  [ [ 0  ∞ ] ]

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--output-tensor-dir / -output-tensor-dir

Directory of training tensors. Subdivided into train, valid and test sets.

R String  null

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--QUIET / NA

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

Boolean  false

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--reference / -R

Reference fasta file.

R String  null

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--showHidden / -showHidden

display hidden arguments

boolean  false

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--tensor-type / -tensor-type

Name of the tensors to generate.

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

reference

read_tensor

TensorType  reference

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--TMP_DIR / NA

Undocumented option

List[File]  []

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--truth-bed / -truth-bed

Confident region of the validated VCF file.

R String  null

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--truth-vcf / -truth-vcf

Validated VCF file.

R String  null

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

Whether to use the JdkDeflater (as opposed to IntelDeflater)

boolean  false

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

Whether to use the JdkInflater (as opposed to IntelInflater)

boolean  false

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--variant / -V

Input VCF file

R String  null

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--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

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--version / NA

display the version number for this tool

boolean  false

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GATK version 4.0.7.0 built at 25-30-2019 01:30:00.