Determines the baseline contig ploidy for germline samples given counts data

Category Copy Number Variant Discovery

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Overview

Determines the integer ploidy state of all contigs for germline samples given counts data. These should be either HDF5 or TSV count files generated by CollectReadCounts; TSV files may be compressed (e.g., with bgzip), but must then have filenames ending with the extension .gz. See the documentation for the input argument for details on enabling streaming of indexed count files from Google Cloud Storage.

Introduction

Germline karyotyping is a frequently performed task in bioinformatics pipelines, e.g. for sex determination and aneuploidy identification. This tool uses counts data for germline karyotyping.

Performing germline karyotyping using counts data requires calibrating ("modeling") the technical coverage bias and variance for each contig. The Bayesian model and the associated inference scheme implemented in DetermineGermlineContigPloidy includes provisions for inferring and explaining away much of the technical variation. Furthermore, karyotyping confidence is automatically adjusted for individual samples and contigs.

Running DetermineGermlineContigPloidy is the first computational step in the GATK germline CNV calling pipeline. It provides a baseline ("default") copy-number state for each contig/sample with respect to which the probability of alternative states is allocated.

Python environment setup

The computation done by this tool, aside from input data parsing and validation, is performed outside of the Java Virtual Machine and using the gCNV computational python module, namely gcnvkernel. It is crucial that the user has properly set up a python conda environment with gcnvkernel and its dependencies installed. If the user intends to run DetermineGermlineContigPloidy using one of the official GATK Docker images, the python environment is already set up. Otherwise, the environment must be created and activated as described in the main GATK README.md file.

Advanced users may wish to set the THEANO_FLAGS environment variable to override the GATK theano configuration. For example, by running THEANO_FLAGS="base_compiledir=PATH/TO/BASE_COMPILEDIR" gatk DetermineGermlineContigPloidy ..., users can specify the theano compilation directory (which is set to $HOME/.theano by default). See theano documentation at http://deeplearning.net/software/theano/library/config.html.

Tool run modes

This tool has two operation modes as described below:

COHORT mode:

If a ploidy model parameter path is not provided via the model argument, the tool will run in the COHORT mode. In this mode, ploidy model parameters (e.g. coverage bias and variance for each contig) are inferred, along with baseline contig ploidy states of each sample. It is possible to run the tool over a subset of all intervals present in the input count files, which can be specified by -L; this can be used to pass a filtered interval list produced by FilterIntervals to mask intervals from modeling. Intervals may also be blacklisted using -XL. The specified intervals that result from resolving -L/-XL inputs must be exactly present in all of the input count files.

A TSV file specifying prior probabilities for each integer ploidy state and for each contig is required in this mode and must be specified via the contig-ploidy-priors argument. The following shows an example of such a table:

CONTIG_NAME	PLOIDY_PRIOR_0	PLOIDY_PRIOR_1	PLOIDY_PRIOR_2	PLOIDY_PRIOR_3
1	0.01	0.01	0.97	0.01
2	0.01	0.01	0.97	0.01
X	0.01	0.49	0.49	0.01
Y	0.50	0.50	0.00	0.00

Note that the contig names appearing under CONTIG_NAME column must match contig names in the input counts files, and all contigs appearing in the input counts files must have a corresponding entry in the priors table. The order of contigs is immaterial in the priors table. The highest ploidy state is determined by the prior table (3 in the above example). A ploidy state can be strictly forbidden by setting its prior probability to 0. For example, the Y contig in the above example can only assume 0 and 1 ploidy states.

If the provided count data only contains intervals from a single chromosome, the model degeneracy in this case will lead to no meaningful inference and the ploidy states will be resolved to the most likely ploidy states given by the ploidy prior table. As an example, autosomal contigs will assume ploidy 2, and X could assume either 1 or 2 depending on tie breakers.

The tool output in the COHORT mode will contain two subdirectories, one ending with "-model" and the other ending with "-calls". The model subdirectory contains the inferred parameters of the ploidy model, which may be used later on for karyotyping one or more similarly-sequenced samples (see below). The calls subdirectory contains one subdirectory for each sample, listing various sample-specific quantities such as the global read-depth, average ploidy, per-contig baseline ploidies, and per-contig coverage variance estimates.

CASE mode:

If a path containing previously inferred ploidy model parameters is provided via the model argument, then the tool will run in the CASE mode. In this mode, the parameters of the ploidy model are loaded from the provided directory and only sample-specific quantities are inferred. The modeled intervals are then specified by a file contained in the model directory, all interval-related arguments are ignored in this mode, and all model intervals must be present in all of the input count files. The tool output in the CASE mode is only the "-calls" subdirectory and is organized similarly to the COHORT mode.

In the CASE mode, the contig ploidy prior table is taken directly from the provided model parameters path and must be not provided again.

Important Remarks

Choice of hyperparameters:

The quality of ploidy model parametrization and the sensitivity/precision of germline karyotyping are sensitive to the choice of model hyperparameters, including standard deviation of mean contig coverage bias (set using the mean-bias-standard-deviation argument), mapping error rate (set using the mapping-error-rate argument), and the typical scale of contig- and sample-specific unexplained variance (set using the global-psi-scale and sample-psi-scale arguments, respectively). It is crucial to note that these hyperparameters are not universal and must be tuned for each sequencing protocol and properly set at runtime.

Mosaicism and fractional ploidies:

The model underlying this tool assumes integer ploidy states (in contrast to fractional/variable ploidy states). Therefore, it is to be used strictly on germline samples and for the purpose of sex determination, autosomal aneuploidy detection, or as a part of the GATK germline CNV calling pipeline. The presence of large somatic events and mosaicism (e.g., sex chromosome loss and somatic trisomy) will naturally lead to unreliable results. We strongly recommended inspecting genotyping qualities (GQ) from the tool output and considering to drop low-GQ contigs in downstream analyses. Finally, given the Bayesian status of this tool, we suggest including as many high-quality germline samples as possible for ploidy model parametrizaton in the COHORT mode. This will downplay the role of questionable samples and will yield a more reliable estimation of genuine sequencing biases.

Coverage-based germline karyotyping:

Accurate germline karyotyping requires incorporating SNP allele-fraction data and counts data in a unified probabilistic model and is beyond the scope of the present tool. The current implementation only uses counts data for karyotyping and while being fast, it may not provide the most reliable results.

Usage examples

COHORT mode:

 gatk DetermineGermlineContigPloidy \
   --input normal_1.counts.hdf5 \
   --input normal_2.counts.hdf5 \
   ... \
   --contig-ploidy-priors a_valid_ploidy_priors_table.tsv
   --output output_dir \
   --output-prefix normal_cohort
 

COHORT mode (with optional interval filtering):

 gatk DetermineGermlineContigPloidy \
   -L intervals.interval_list \
   -XL blacklist_intervals.interval_list \
   --interval-merging-rule OVERLAPPING_ONLY \
   --input normal_1.counts.hdf5 \
   --input normal_2.counts.hdf5 \
   ... \
   --contig-ploidy-priors a_valid_ploidy_priors_table.tsv
   --output output_dir \
   --output-prefix normal_cohort
 

CASE mode:

 gatk DetermineGermlineContigPloidy \
   --model a_valid_ploidy_model_dir
   --input normal_1.counts.hdf5 \
   --input normal_2.counts.hdf5 \
   ... \
   --output output_dir \
   --output-prefix normal_case
 

DetermineGermlineContigPloidy 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		Input paths for read-count files containing integer read counts in genomic intervals for all samples. All intervals specified via -L/-XL must be contained; if none are specified, then intervals must be identical and in the same order for all samples. If read-count files are given by Google Cloud Storage paths, have the extension .counts.tsv or .counts.tsv.gz, and have been indexed by IndexFeatureFile, only the specified intervals will be queried and streamed; this can reduce disk usage by avoiding the complete localization of all read-count files.
--output  -O		Output directory. This will be created if it does not exist.
--output-prefix		Prefix for output filenames.
Optional Tool Arguments
--adamax-beta-1	0.9	Adamax optimizer first moment estimation forgetting factor.
--adamax-beta-2	0.999	Adamax optimizer second moment estimation forgetting factor.
--arguments_file		read one or more arguments files and add them to the command line
--caller-external-admixing-rate	0.75	Admixing ratio of new and old called posteriors (between 0 and 1; larger values implies using more of the new posterior and less of the old posterior) after convergence.
--caller-internal-admixing-rate	0.75	Admixing ratio of new and old called posteriors (between 0 and 1; larger values implies using more of the new posterior and less of the old posterior) for internal convergence loops.
--caller-update-convergence-threshold	0.001	Maximum tolerated calling update size for convergence.
--contig-ploidy-priors		Input file specifying contig-ploidy priors. If only a single sample is specified, this input should not be provided. If multiple samples are specified, this input is required.
--convergence-snr-averaging-window	5000	Averaging window for calculating training signal-to-noise ratio (SNR) for convergence checking.
--convergence-snr-countdown-window	10	The number of ADVI iterations during which the SNR is required to stay below the set threshold for convergence.
--convergence-snr-trigger-threshold	0.1	The SNR threshold to be reached before triggering the convergence countdown.
--disable-annealing	false	(advanced) Disable annealing.
--disable-caller	false	(advanced) Disable caller.
--disable-sampler	false	(advanced) Disable sampler.
--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.
--global-psi-scale	0.001	Prior scale of contig coverage unexplained variance. If a single sample is provided, this input will be ignored.
--help  -h	false	display the help message
--initial-temperature	2.0	Initial temperature (for DA-ADVI).
--interval-merging-rule  -imr	ALL	Interval merging rule for abutting intervals
--intervals  -L		One or more genomic intervals over which to operate
--learning-rate	0.05	Adamax optimizer learning rate.
--log-emission-samples-per-round	2000	Log emission samples drawn per round of sampling.
--log-emission-sampling-median-rel-error	5.0E-4	Maximum tolerated median relative error in log emission sampling.
--log-emission-sampling-rounds	100	Log emission maximum sampling rounds.
--mapping-error-rate	0.01	Typical mapping error rate.
--max-advi-iter-first-epoch	1000	Maximum ADVI iterations in the first epoch.
--max-advi-iter-subsequent-epochs	1000	Maximum ADVI iterations in subsequent epochs.
--max-calling-iters	1	Maximum number of internal self-consistency iterations within each calling step.
--max-training-epochs	100	Maximum number of training epochs.
--mean-bias-standard-deviation	0.01	Prior standard deviation of the contig-level mean coverage bias. If a single sample is provided, this input will be ignored.
--min-training-epochs	20	Minimum number of training epochs.
--model		Input ploidy-model directory. If only a single sample is specified, this input is required. If multiple samples are specified, this input should not be provided.
--num-thermal-advi-iters	5000	Number of thermal ADVI iterations (for DA-ADVI).
--sample-psi-scale	1.0E-4	Prior scale of the sample-specific correction to the coverage unexplained variance.
--version	false	display the version number for this tool
Optional Common Arguments
--exclude-intervals  -XL		One or more genomic intervals to exclude from processing
--gatk-config-file		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.
--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
--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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--adamax-beta-1

Adamax optimizer first moment estimation forgetting factor.

double  0.9  [ [ 0  1 ] ]

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--adamax-beta-2

Adamax optimizer second moment estimation forgetting factor.

double  0.999  [ [ 0  1 ] ]

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--arguments_file

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

List[File]  []

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--caller-external-admixing-rate

Admixing ratio of new and old called posteriors (between 0 and 1; larger values implies using more of the new posterior and less of the old posterior) after convergence.

double  0.75  [ [ 0  ∞ ] ]

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--caller-internal-admixing-rate

Admixing ratio of new and old called posteriors (between 0 and 1; larger values implies using more of the new posterior and less of the old posterior) for internal convergence loops.

double  0.75  [ [ 0  ∞ ] ]

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--caller-update-convergence-threshold

Maximum tolerated calling update size for convergence.

double  0.001  [ [ 0  ∞ ] ]

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--contig-ploidy-priors

Input file specifying contig-ploidy priors. If only a single sample is specified, this input should not be provided. If multiple samples are specified, this input is required.

File  null

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--convergence-snr-averaging-window

Averaging window for calculating training signal-to-noise ratio (SNR) for convergence checking.

int  5000  [ [ 0  ∞ ] ]

---

--convergence-snr-countdown-window

The number of ADVI iterations during which the SNR is required to stay below the set threshold for convergence.

int  10  [ [ 0  ∞ ] ]

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--convergence-snr-trigger-threshold

The SNR threshold to be reached before triggering the convergence countdown.

double  0.1  [ [ 0  ∞ ] ]

---

--disable-annealing

(advanced) Disable annealing.

boolean  false

---

--disable-caller

(advanced) Disable caller.

boolean  false

---

--disable-sampler

(advanced) Disable sampler.

boolean  false

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--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]  []

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--gatk-config-file

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  [ [ -∞  ∞ ] ]

---

--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  ""

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--global-psi-scale

Prior scale of contig coverage unexplained variance. If a single sample is provided, this input will be ignored.

double  0.001  [ [ 0  ∞ ] ]

---

--help / -h

display the help message

boolean  false

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--initial-temperature

Initial temperature (for DA-ADVI).

double  2.0  [ [ 0  ∞ ] ]

---

--input / -I

Input paths for read-count files containing integer read counts in genomic intervals for all samples. All intervals specified via -L/-XL must be contained; if none are specified, then intervals must be identical and in the same order for all samples. If read-count files are given by Google Cloud Storage paths, have the extension .counts.tsv or .counts.tsv.gz, and have been indexed by IndexFeatureFile, only the specified intervals will be queried and streamed; this can reduce disk usage by avoiding the complete localization of all read-count files.

R List[String]  []

---

--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  [ [ -∞  ∞ ] ]

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--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

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--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  [ [ -∞  ∞ ] ]

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--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

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--intervals / -L

One or more genomic intervals over which to operate

List[String]  []

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--learning-rate

Adamax optimizer learning rate.

double  0.05  [ [ 0  ∞ ] ]

---

--log-emission-samples-per-round

Log emission samples drawn per round of sampling.

int  2000  [ [ 0  ∞ ] ]

---

--log-emission-sampling-median-rel-error

Maximum tolerated median relative error in log emission sampling.

double  5.0E-4  [ [ 0  ∞ ] ]

---

--log-emission-sampling-rounds

Log emission maximum sampling rounds.

int  100  [ [ 0  ∞ ] ]

---

--mapping-error-rate

Typical mapping error rate.

double  0.01  [ [ 0  1 ] ]

---

--max-advi-iter-first-epoch

Maximum ADVI iterations in the first epoch.

int  1000  [ [ 0  ∞ ] ]

---

--max-advi-iter-subsequent-epochs

Maximum ADVI iterations in subsequent epochs.

int  1000  [ [ 0  ∞ ] ]

---

--max-calling-iters

Maximum number of internal self-consistency iterations within each calling step.

int  1  [ [ 0  ∞ ] ]

---

--max-training-epochs

Maximum number of training epochs.

int  100  [ [ 0  ∞ ] ]

---

--mean-bias-standard-deviation

Prior standard deviation of the contig-level mean coverage bias. If a single sample is provided, this input will be ignored.

double  0.01  [ [ 0  ∞ ] ]

---

--min-training-epochs

Minimum number of training epochs.

int  20  [ [ 0  ∞ ] ]

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--model

Input ploidy-model directory. If only a single sample is specified, this input is required. If multiple samples are specified, this input should not be provided.

File  null

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--num-thermal-advi-iters

Number of thermal ADVI iterations (for DA-ADVI).

int  5000  [ [ 0  ∞ ] ]

---

--output / -O

Output directory. This will be created if it does not exist.

R File  null

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--output-prefix

Prefix for output filenames.

R String  null

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--QUIET

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

Boolean  false

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--sample-psi-scale

Prior scale of the sample-specific correction to the coverage unexplained variance.

double  1.0E-4  [ [ 0  ∞ ] ]

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--showHidden / -showHidden

display hidden arguments

boolean  false

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--tmp-dir

Temp directory to use.

GATKPath  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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--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

display the version number for this tool

boolean  false

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GATK version 4.1.9.0-SNAPSHOT built at Mon, 19 Oct 2020 11:41:12 -0400.