Apply a Convolutional Neural Net to filter annotated variants
Category Variant Filtering
Overview
Annotate a VCF with scores from a Convolutional Neural Network (CNN). This tool streams variants and their reference context to a python program, which evaluates a pre-trained neural network on each variant. The default models were trained on single-sample VCFs. The default model should not be used on VCFs with annotations from joint call-sets. The neural network performs convolutions over the reference sequence surrounding the variant and combines those features with a multilayer perceptron on the variant annotations. 2D models convolve over aligned reads as well as the reference sequence, and variant annotations. 2D models require a SAM/BAM file as input and for the --tensor-type argument to be set to a tensor type which requires reads, as in the example below. Pre-trained 1D and 2D models are included in the distribution. It is possible to train your own models with the tools: CNNVariantWriteTensors and CNNVariantTrain. CNNVariantTrain will create a json architecture file and an hd5 weights file, which you can use with this tool. The advanced argument `info-annotation-keys` is available for models trained with different sets info field annotations. In order to do this you must first train your own model with the tools CNNVariantWriteTensors and CNNVariantTrain. Otherwise, providing this argument with anything but the standard set of annotations will result in an error.1D Model with pre-trained architecture
gatk CNNScoreVariants \ -V vcf_to_annotate.vcf.gz \ -R reference.fasta \ -O annotated.vcf
2D Model with pre-trained architecture
gatk CNNScoreVariants \ -I aligned_reads.bam \ -V vcf_to_annotate.vcf.gz \ -R reference.fasta \ -O annotated.vcf \ -tensor-type read-tensor
1D Model with user-supplied architecture and weights:
gatk CNNScoreVariants \ -V vcf_to_annotate.vcf.gz \ -R reference.fasta \ -O annotated.vcf \ -architecture path/to/my_model_folder/1dmodel.json -weights path/to/my_model_folder/1dmodel.hd5
2D Model with user-supplied model architecture and weights:
gatk CNNScoreVariants \ -I aligned_reads.bam \ -V vcf_to_annotate.vcf.gz \ -R reference.fasta \ -O annotated.vcf \ -tensor-type read-tensor \ -architecture path/to/my_model_folder/2dmodel.json -weights path/to/my_model_folder/2dmodel.hd5
Additional Information
Read filters
These Read Filters are automatically applied to the data by the Engine before processing by CNNScoreVariants.
CNNScoreVariants 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 -O |
Output file | ||
--reference -R |
Reference sequence file | ||
--variant -V |
A VCF file containing variants | ||
Optional Tool Arguments | |||
--architecture |
Neural Net architecture configuration json file | ||
--arguments_file |
read one or more arguments files and add them to the command line | ||
--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). | |
--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! | |
--filter-symbolic-and-sv |
false | If set will filter symbolic and and structural variants from the input VCF | |
--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. | ||
--help -h |
false | display the help message | |
--interval-merging-rule -imr |
ALL | Interval merging rule for abutting intervals | |
--intervals -L |
One or more genomic intervals over which to operate | ||
--read-limit |
128 | Maximum number of reads to encode in a tensor, for 2D models only. | |
--sites-only-vcf-output |
false | If true, don't emit genotype fields when writing vcf file output. | |
--tensor-type |
reference | Name of the tensors to generate, reference for 1D reference tensors and read_tensor for 2D tensors. | |
--version |
false | display the version number for this tool | |
--weights |
Keras model HD5 file with neural net weights. | ||
--window-size |
128 | Neural Net input window size | |
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. | ||
--input -I |
BAM/SAM/CRAM file containing reads | ||
--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 | |
--max-variants-per-shard |
0 | If non-zero, partitions VCF output into shards, each containing up to the given number of records. | |
--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 | |||
--disable-avx-check |
false | If set, no check will be made for AVX support. Use only if you have installed a pre-1.6 TensorFlow build. | |
--inference-batch-size |
256 | Size of batches for python to do inference on. | |
--info-annotation-keys |
[MQ, DP, SOR, FS, QD, MQRankSum, ReadPosRankSum] | The VCF info fields to send to python. This should only be changed if a new model has been trained which expects the annotations provided here. | |
--inter-op-threads |
0 | Number of inter-op parallelism threads to use for Tensorflow | |
--intra-op-threads |
0 | Number of intra-op parallelism threads to use for Tensorflow | |
--output-tensor-dir |
Optional directory where tensors can be saved for debugging or visualization. | ||
--showHidden |
false | display hidden arguments | |
--transfer-batch-size |
512 | Size of data to queue for python streaming. |
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.
--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
--architecture / -architecture
Neural Net architecture configuration json file
String null
--arguments_file
read one or more arguments files and add them to the command line
List[File] []
--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 [ [ -∞ ∞ ] ]
--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
--disable-avx-check / -disable-avx-check
If set, no check will be made for AVX support. Use only if you have installed a pre-1.6 TensorFlow build.
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-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 (WARNING: many tools will not function correctly without their default read filters on)
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] []
--filter-symbolic-and-sv / -filter-symbolic-and-sv
If set will filter symbolic and and structural variants from the input VCF
boolean false
--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 ""
--help / -h
display the help message
boolean false
--inference-batch-size / -inference-batch-size
Size of batches for python to do inference on.
int 256 [ [ 1 4,096 ] ]
--info-annotation-keys / -info-annotation-keys
The VCF info fields to send to python. This should only be changed if a new model has been trained which expects the annotations provided here.
List[String] [MQ, DP, SOR, FS, QD, MQRankSum, ReadPosRankSum]
--input / -I
BAM/SAM/CRAM file containing reads
List[GATKPath] []
--inter-op-threads / -inter-op-threads
Number of inter-op parallelism threads to use for Tensorflow
int 0 [ [ 0 4,096 ] ]
--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] []
--intra-op-threads / -intra-op-threads
Number of intra-op parallelism threads to use for Tensorflow
int 0 [ [ 0 4,096 ] ]
--lenient / -LE
Lenient processing of VCF files
boolean false
--max-variants-per-shard
If non-zero, partitions VCF output into shards, each containing up to the given number of records.
int 0 [ [ 0 ∞ ] ]
--output / -O
Output file
R GATKPath null
--output-tensor-dir / -output-tensor-dir
Optional directory where tensors can be saved for debugging or visualization.
String ""
--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-limit / -read-limit
Maximum number of reads to encode in a tensor, for 2D models only.
int 128 [ [ 0 ∞ ] ]
--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
--reference / -R
Reference sequence file
R GATKPath null
--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.
GATKPath 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
--tensor-type / -tensor-type
Name of the tensors to generate, reference for 1D reference tensors and read_tensor for 2D tensors.
The --tensor-type argument is an enumerated type (TensorType), which can have one of the following values:
- reference
- 1 Hot encoding of a reference sequence.
- read_tensor
- Read tensor are 3D tensors spanning aligned reads, sites and channels. The maximum number of reads is a hyper-parameter typically set to 128. There are 15 channels in the read tensor. They correspond to the reference sequence data (4), read sequence data (4), insertions and deletions (2) read flags (4) and mapping quality (1).
TensorType reference
--tmp-dir
Temp directory to use.
GATKPath null
--transfer-batch-size / -transfer-batch-size
Size of data to queue for python streaming.
int 512 [ [ 1 8,192 ] ]
--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
--variant / -V
A VCF file containing variants
R GATKPath null
--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
--weights / -weights
Keras model HD5 file with neural net weights.
String null
--window-size / -window-size
Neural Net input window size
int 128 [ [ 0 ∞ ] ]
GATK version 4.2.5.0-SNAPSHOT built at Mon, 7 Feb 2022 11:18:01 -0500.
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