* Removed unused annotations (CCC and HWP)
* Renamed one of the two GC annotations to "IGC" (for Interval GC)
* Revved picard & htsjdk (GATK constants are now removed from htsjdk)
* PT 82046038
-- Active Region Traversal was using per sample limits on the number of reads that were too low, especially now that we are running one sample at a time. This caused issues with high confidence variants being dropped in high coverage data.
-- HaplotypeCallerGVCFIntegrationTest PL/annotation changes due to using more reads in those tests
-- Removed a CountReadsInActiveRegionsIntegrationTest test for excessive coverage because the read coverage no longer goes over the limits in ART
Story:
=====
- https://www.pivotaltracker.com/story/show/83803796
Changes:
=======
- From a fix maximum ploidy indel RCM likelihood cache to a
dynamically resizable one.
- Used the occassion to removed an unused and deprecated method from ReferenceConfidenceModel
Testing:
=======
- Added integration test to check on ploidies larger than the previous limit of 20.
Add multi-allele test for info field annotations
Fix to process all types of INFO annotations
roll back to previous version, removes INFO and FORMAT
Correct @return for VariantAnnotatorEngine.getNonReferenceAlleles()
Enhance comments and clean up multi-allelic logic, handle header info number = R
only parse counts of A & R
Add INFO for AC
update MD5
Performance enhancement, only parse multiallelic with a count A or R
Make argument final in getNonReferenceAlleles()
Code cleanup, add exceptions for bad expression/allele size mismatch and missing header info for an expression
Change exception to warning for expression value/number of alleles check
remove adevertised exceptions
-- Ignore SNP matches that lie outside the clipped read window
-- This fixes an issue where GATK would skip the entire read if a SNP is entirely
contained within a sequencing adapter.
Story:
=====
- https://www.pivotaltracker.com/story/show/83259038
Changes:
=======
- Done minimal changes to make the fix after an arduous attempt to understand
CombineGVCFs code.
Test:
====
- Added a integration test to explicitly test for the bug.
- Updated a md5 changes as the bug was actually affecting one of the existing
integration tests.
* PT 84242218
* Note that FORMAT fields behave the same as INFO fields - if the annotation has a count of A (one entry per Alt Allele), it is split across the multiple output lines. Otherwise, the entire list is output with each field
Story:
-----
- https://www.pivotaltracker.com/story/show/83800586
Changes:
-------
- In GVCFWriter GQ is now recalculated out of the fianl PL array for the block.
Testing:
-------
- Updated affected integration test md5s
Add more logging to annotators, change loggers from info to warn
Add comments to testStrandBiasBySample()
Clarify comments in testStrandBiasBySample
remove logic for not prcossing an indel if strand bias (SB) was not computed
remove per variant warnings in annotate()
Log warnings if using the wrong annotator or missing a pedgree file
Log test failures once in annotate(), because HaplotypeCaller does not call initialize(). Avoid using exceptions
Fix so only log once in annotate(), Hardey-Weinberg does not require pedigree files, fix test MD5s so pass
Check if founderIds == null
Update MD5s from HaplotypeCaller integrations tests and clean up code
Change logic so SnpEff does not throw excpetions, change engine to utils in imports
Update test MD5s, return immediately if cannot annotate in SnpEff.initialization()
Post peer review, add more logging warnings
Update MD5 for testHaplotypeCallerMultiSampleComplex1, return null if PossibleDeNovo.annotate() is not called by VariantAnnotator
Story:
-----
https://www.pivotaltracker.com/story/show/80684230
Changes:
-------
- Corrected the bug: AlignmentUtils#createReadAlignedToRef was
not realigning against the reference but the best haplotype for
the read.
Test:
----
- Added integration test in HaplotypeCallerIntegrationTest to check
that the bug has been fixed.
- Fixed md5s modified by this change; these are cause due to small
changes in the state of the random-number generator and read vs
variant site overlapping.
CombineGVCFs now outputs ref conf for the duration of deletions so that SNPs occuring in other samples aligned with those deletions will be genotyped correctly
Reading the multiple GATKText files as a single stream, especially with new top level target executable jar files pointing to a lib folder.
Don't dirty the build with a new GATKText.properties if input files are unmodified.
Stop warning on undocumented abstract classes.
Fixed ClassNotFoundException/NoClassDefFoundError by fixing ResourceBundleExtractorDoclet artifact.
Excluding Exceptions from documentation.
Removed custom log4j dependency from ResourceBundleExtractorDoclet.
Stop generating the dependency reduced pom during shade.
Stop regenerating gsalib when the files are already up to date.
Disabled mvn site generation from external-example.
Moved top level target symlinks to package jar files to under target/package.
Executable jar files are placed under target/executable with the new target[/lib] directories.
Under top level target, symlinks to *either* the package *or* the executable jars replace what was a symlink to the package jar path.
Allow disabling of the shade package.
ant-bridge.sh by default only builds executable jars, and doesn't package by default, as did the old ant build.xml.
Added a new package_path.sh utility script for other scripts to use instead of anything in the target folder.
remove final keyword before refMap and altMap, constructHaplotype() changes their values
return ArtificialHaplotype from constructHaplotype instaed of passing as an argument
Add logic so arraycopy does not throw an IndexOutOfBoundsException, add test for a long insert
* This argument is intended to be used in conjunction with -bamout, and disable early-exit optimizations to allow reference regions to be contained in the output bam
* Also forcibly includes the reference haplotype in the set of haplotypes given to the BAMWriter
* Made -dontTrimActiveRegions visible, as it is likely also desirable in this use case
* Addresses PT 77731660
remove TODO comment after activeProbThreshold
recover static ACTIVE_PROB_THRESHOLD for unit tests
Add min/max values for active_probability_threshold parameter
Move activeProbThreshold parameter to GATKArguemtnCollection
define ACTIVE_PROB_THRESHOLD in unit tests
add construction of argCollection in in ctor
Move arguments from GATKArgumentCollection to ActiveRegionWalker
Throw exception if threshold < 0 or > 1 in ActivityProfile ctor
max propogation distance parameter to ActiveRegionWalker for AcrtivityProfile
Use polymorphic getMaxProbPropagationDistance() so BandPassActivityProfile computes the crrect region size cutoff
Get the maxProbPropagationDistance from the super class's method, instead of directly, this is safer
Removed extraneous command line imports and make maxProbPropagationDistance a hidden argument
remove limit check for activeProbThreshold, not necessary because the check is made when imput as a command line arg
Remove extra 'region' in the doxygen param description for maxProbPropagationDistance
Rename parameters using camel case and add to integration test
Correct documentation for maxReadsInRegionPerSample and minReadsPerAlignmentStart
Change the argument--minReadsPerAlignmentStart in the integration test from 50 to 5
'each genomic location' only pertains to minReadsPerAlignmentStart, not maxReadsInRegionPerSample
The QUAL value calculated by this Exact AF Calculator is very underestimated when
there are more than one alternative allele (non-biallelic sites). The reason is
that the QUAL was roughly calculated by adding the QUALs resulting of each alternative
alleles vs all other alleles, reference and alts, collapsed. This is ok for MLEAC
calculations but not for QUAL.
Now, for calculating the QUAL we collapse all the alternatives as only one. This change
improves sensitivy with a cost of additional false positives, but this is naturally expected.
The resulting QUAL column is much closer to the one returned by the reference implementation.
Story:
https://www.pivotaltracker.com/story/show/75926368.
Changes:
Changed the QUAL calculation as described above.
Updated MD5s.
Fixed MD5s
The problem whas that the MLE table calculation aborted "unlikely"
genotype combinations to aggresively.
This also uncovered another bug where GeneralPloidyExactAFCalculation
makes a slightly different use of StateTracker
as compared to DiploidExactAFCalculation. We have changed StateTracker
generalizing it to be able to work with both using code behaviors.
Story:
-----
* https://www.pivotaltracker.com/story/show/78920568
Changes:
-------
* Fixes in GeneralPloidyExactAFCalculator.
* Needed changes in StateTracker API and its consequences in DiploidExactAFCalculation.
* Updated affected integrated tests' MD5s after fixing the GeneralPloidyExactAF.
Changes:
-------
* Updated current unit and integration test to use the new API components.
* Added unit tests for new classes AFPriorProvider and AFCalculatorProviders.
* Added integration test for mixed ploidy GenotypeGVCFs and CombineGVCFs
Changes:
-------
* GenotypingEngine uses now a AFCalc provider instead of
its own thread-local with one-time initialized and fixed
AF calculator.
* All walkers that use a GenotypingEngine now are passing
the appropiate AF calculator provider. For now most
just use a fix calculator (FixedAFCalculatorProvider)
except GenotypeGVCFs as this one now can cope with
mixture of ploidies failing-over to a general-ploidy
calculator when the preferred implementation is not
capable to handle a site's analysis.
to the total-ploidy (added ploidy accross samples).
Changes:
--------
* Instead of calculate a fixed log10 prior array with a fix
total likelihood we use a new component, the AFPriorProvider
to generate the priors for different total plodies on
demand; these are cached however so there is no unecessary
recompute involved.
with mixed ploidies and max-alt-allele number changes dynamically.
Changes:
--------
* Moved the AFCalcFactory.Calculation enum in a top level class
AFCalculatorImplementation.
* Given more reponsabilities to the enum like resolving the constructor
method once per implementation and the best-model selection algorithm.
* Removed test-code only fields and methods from AFCalc; just used to perform
unit-testing and not any actual functionality of this component.
* Removed the fixed ploidy constraint of GeneralPloidyExactAFCalc
implementation... now can deal with mixed ploidies that may change
per site and sample.
* Removed the fixed maxAltAllele restriction by allowing resizing of
the stateTracker structures.
* Due to previous two points now call the the AFCalc object are passed
the default-ploidy to assume in case some genotype in the input
VC does not have it and the max-alt-allele.
* Also due to those changes, removed the now totally useless 3 int
parameters from all AFCalc constructors.
* Cleaned the code a bit from no further used components and methods.
Dangling head merging (like with tails) in now enabled by default.
The --recoverDanglingHeads argument is now deprecated so that users know not to use it anymore.
We now also allow the user to set the minimum branch length for merging. This will be different
for exomes and RNA (see below).
The other changes in the code itself:
1. We no longer allow an arbitrarily large number of mismatches in the dangling head for merging
2. The max number of mismatches allowed in a dangling head is proportional to the kmer size
There will be a difference in the RNA calling pipeline. Instead of invoking '--recoverDanglingHeads'
the user will instead want to use '--minDanglingBranchLength 0'.
Below are the knowledgebase results of the master branch vs. this one.
For NA12878 DNA Exome:
master SNPS TRUE_POSITIVE 36722
master SNPS CALLED_NOT_IN_DB_AT_ALL 2699
master SNPS REASONABLE_FILTERS_WOULD_FILTER_FP_SITE 292
master SNPS FALSE_POSITIVE_SITE_IS_FP 70
branch SNPS TRUE_POSITIVE 36867
branch SNPS CALLED_NOT_IN_DB_AT_ALL 2952
branch SNPS REASONABLE_FILTERS_WOULD_FILTER_FP_SITE 387
branch SNPS FALSE_POSITIVE_SITE_IS_FP 94
As I discussed with Ryan in person, there are a good number of FPs that are called in the new
code, but they nearly all have bad strand bias and should be easily filtered by VQSR.
Note that there is no change for indels.
For NA12878 RNA from Ami:
master SNPS TRUE_POSITIVE 11055
master SNPS CALLED_NOT_IN_DB_AT_ALL 831
master SNPS REASONABLE_FILTERS_WOULD_FILTER_FP_SITE 44
master SNPS FALSE_POSITIVE_SITE_IS_FP 96
branch SNPS TRUE_POSITIVE 11113
branch SNPS CALLED_NOT_IN_DB_AT_ALL 874
branch SNPS REASONABLE_FILTERS_WOULD_FILTER_FP_SITE 47
branch SNPS FALSE_POSITIVE_SITE_IS_FP 92
Again, there's basically no change for indels.
* Arguments involved are --no_cmdline_in_header, --sites_only, and --bcf for VCF files and --bam_compression, --simplifyBAM, --disable_bam_indexing, and --generate_md5 for BAM files
* PT 52740563
* Removed ReadUtils.createSAMFileWriterWithCompression(), replaced with ReadUtils.createSAMFileWriter(), which applies all appropriate engine-level arguments
* Replaced hard-coded field names in ArgumentDefinitionField (Queue extension generator) with a Reflections-based lookup that will fail noisily during extension generation if there's an error
Explicitly including gatk/queue test-jar artifacts in package test classpaths.
SelectVariantsIntegrationTest#testInvalidJexl now resets the JexlEngine silent flag that VariantFiltration.initialize() toggles.
External example no longer tries to unpack nonexistent gatk artifact jars during package tests.
Same changes fixed the problem for GenotypeGVCFs and CombineGVCFs.
Stories:
- https://www.pivotaltracker.com/story/show/77626044
- https://www.pivotaltracker.com/story/show/77626854
Changes:
- Generalized the code for the merging in GATKVariantContextUtils to cope
with ploidy != 2.
- GenotypeGVCFs now check that the input's ploidy conform to the '-ploidy'
argument.
- Moved out Refernce Confidence VC merging code from GATKVariantContextUtils
so that we can keep new code in protected.
Caveats:
- GenotypeGVCFs only can deal with input files that have the same ploidy in
all positions; the one that the user MUST indicate in the -ploidy argument
(if different to the default 2).
- CombineGVCFs won't necessarely complain if its passed mixed ploidy
inputs but you won't be able to genotype it with GenotypeGVCFs.
Test:
- Removed deprecated unit tests for GATKVariantContextUtils.
- Moved unit-tests regarding GVCF merging from GATKVariantContextUtilsUnitTest
to ReferenceConfidenceVariantContextUtilsUnitTest.
- Added unit test for new code for mapping genotype indices between allele
index encoding in GenotypeLikelihoodCalculator.
- GenotypeGVCFs and CombineGVCFs original integration test are unaffected
by the change.
- Added tetraploid run integration tests to check on non-diploid execution
of GenotypeGVCFs and CombineGVCFs.
Changed tests and scripts to use gatkdir full path instead of relative testdata/qscripts symbolic links.
Although symlinks not created, left the symlink deletion script execution with a comment about future removal.
Re-enabled example UG pipeline queue test.
Replaced all hardcoded strings of {public,private}/testdata with BaseTest variables.
Refactored temp list creation method from ListFileUtilsUnitTest to BaseTest.createTempListFile.
Removed list files with hardcoded paths, now using createTempListFile instead with private test dir variable.
We do this for technical reasons, mostly because we don't genotype in the HC anymore; it's all
done downstream by GenotypeGVCFs so we can't be sure that the genotype will be hom var. Also,
there are steps in the downstream pipeline where genotypes can change, so assuming anything in
the HC is a bad idea, and if we have phasing info in the het state, we want to propagate that forward.
Now, PGT tag fixing happens downstream in GenotypeGVCFs.
While I was in there I also cleaned up the code a bit and fixed a bug where annotation was happening
before genotype creation when using the --includeNonVariantSites argument.
Added tests accordingly.
* This is a shortcut for people who have multi-sample BAMs but would like to use GVCF mode. Rather than creating single-sample BAMs with PrintReads, one could use the --sample_name argument to HaplotypeCaller to specify the single sample to make calls on
* Completes PT 73075482
Story:
https://www.pivotaltracker.com/story/show/77250524
Changes:
- Remove the annotating code in GeneralPloidyExactAFCalc (GPEAFC) class.
- Added the asAlleleList to GenotypeAlleleCounts class and get (GPEAFC) to use that instead of implementing its own (nicer and more reusable code).
- Removed the explicit addition of AlleleCountBySample fields to the VCF header by the walker initialize
- Added utility methods in Utils to wrap and int[] array into a List<Integer>, and double[] array into a List<Double> efficiently.
Test:
- Added unit-testing for asAlleleList in GenotypeAlleleCountsUnitTest (within testFirst and testNext).
- Added unit-testing for new methods in Utils : asList(int[]) and asList(double[])
- Changed UG General Ploidy test to add explicitly those annotations.
- Non-trivial changes in integration tests involving non-diploid runs (namelly haploid and tetraploid) as they are not showing
those annotations anylonger, so the MD5s have been changed accordingly.
It turns out that there can be some really complex situations even with a single sample where
there are lots of unphasable hets around a hom. Previously we were trying to phase each of the
hets against the hom, but that wasn't correct. Instead we now detect that situation and don't
attempt to phase anything.
Added a unit test to cover this situation.
New annotation for low= and high-confidence de novos (only annotates biallelics)
FamilyLikelihoodsUtils now add joint likelihood and joint posterior annotations
Restrict population priors based on discovered allele count to be valid for 10 or more samples.
VariantAnnotator/FS behavior changes slightly: VA used to output zeros for FS if there was no strand bias info, now skips FS output (but will still show FS in header)
Changes in several walker to use new sample, allele closed lists and new GenotypingEngine constructors signatures
Rebase adoption of new calculation system in walkers
1. It is now turned on by default
2. It now phases homozygous variants
3. Most importantly, it also phases variants that are always on opposite haplotypes
Changed the INFO keys to be PID and PGT, as described in the header.
If any pair of variants occurs on all used haplotypes together, then we propagate that information into the gVCF.
Can be enabled with the --tryPhysicalPhasing argument.
Stories:
https://www.pivotaltracker.com/story/show/70222086https://www.pivotaltracker.com/story/show/67961652
Changes:
Done some changes that I missed in relation with making sure that all PairHMM implentations use the same interface; as a consequence we were running always the standard PairHMM.
Fixed some additional bugs detected when running it on full wgs single sample and exom multi sample data set.
Updated some integration test md5s.
Stories:
https://www.pivotaltracker.com/story/show/70222086https://www.pivotaltracker.com/story/show/67961652
Changes:
Done some changes that I missed in relation with making sure that all PairHMM implentations use the same interface; as a consequence we were running always the standard PairHMM.
Fixed some additional bugs detected when running it on full wgs single sample and exom multi sample data set.
Updated some integration test md5s.
Fixing GraphBased bugs with new master code
Fixed ReadLikelihoods.changeReads difficult to spot bug.
Changed PairHMM interface to fix a bug
Fixed missing changes for various PairHMM implementations to get them to use the new structure.
Fixed various bugs only detectable when running with full sample(s).
Believe to have fixed the lack of annotations in UG runs
Fixed integrationt test MD5s
Updating some md5s
Fixed yet another md5 probably left out by mistake
The array structure should be faster to populate and query (no properly benchmarked) and reduce memory footprint considerably.
Nevertheless removing PairHMM factor (using likelihoodEngine Random) it only achieves a speed up of 15% in some example WGS dataset
i.e. there are other bigger bottle necks in the system. Bamboo tests also seem to run significantly faster with this change.
Stories:
https://www.pivotaltracker.com/story/show/70222086https://www.pivotaltracker.com/story/show/67961652
Changes:
- ReadLikelihoods added to substitute Map<String,PerSampleReadLikelihoods>
- Operation that involve changes in full sets of ReadLikelihoods have been moved into that class.
- Simplified a bit the code that handles the downsampling of reads based on contamination
Caveats:
- Still we keep Map<String,PerReadAlleleLikelihoodsMap> around to pass to annotators..., didn't feel like change the interface of so many public classes in this pull-request.
In particular, it was possible to specify arguments for Files or Compound types without values
Added a special "none" value for annotations, since a bare "-A" is no longer allowed
Delivers PT 71792842 and 59360374
Story:
https://www.pivotaltracker.com/story/show/73440292
Changes:
- Just add the conditional in HaplotypeCaller#initialize
Testing:
- Nothing added, checked locally, trivial change that would eventually be removed anyway.
Don't expand out source nodes for tail merging, since that's a head merging action only.
This shows up as a bug only because we now allow merging tails against non-reference paths.
- Edited intervals merging docs for correctness & clarity
- Edited VQSR arg docs and made mode required (+added -mode SNP to VQSR tests)
- Moved PaperGenotyper to Toy Walkers to declutter the actually useful docs
- Moved GenotypeGVCFs to Variant Discovery category and clarified a few points
- Clarified that the -resource argument depends on using the -V:tag format
- Clarified how the pcr indel model works
- Added caveat for -U ALLOW_N_CIGAR_READS
- Added MathJax support for displaying equations in GATKDocs
- Updated HC example commands and caveats
This is useful for e.g. cases where there are SNPs on insertions. Before tails were forced to be merged
(incorrectly) only to a reference node, but now they can be merged to any path in the graph from which they
directly branch.
Also, I've transferred over Ryan's code to refuse to process kmer sizes such that there are non-unique kmers
in the reference sequence with them.
-- Global mismapping penalty was only applied to the reference haplotype. This led to problems with overlapping events, mostly STR haplotypes. Now the penalty is applied to every haplotype.
-- We subset the reads down to only those which overlap the event (after assembly based realignment) for likelihood calculations.
In these cases, where the alignment contains multiple indels, we output a single complex
variant instead of the multiple partial indels.
We also re-enable dangling tail recovery by default.
-- AD,DP will now correspond directly to the reads that were used to construct the PLs
-- RankSumTests, etc. will use the bases from the realigned reads instead of the original alignments
-- There is now no additional runtime cost to realign the reads when using bamout or GVCF mode
-- bamout mode no longer sets the mapping quality to zero for uninformative reads, instead the read will not be given an HC tag
(Right now it only works if all members of the trio are called.)
Takes posteriors as input, defaulting to PLs
Added annotations for possible de novos for us in full genotype refinement pipeline
Added family priors to CGP integration test.
Changed CGP to use PP tag instead of GP tag because posteriors are Phred-scaled. Updated CGP integration test md5s to reflect change.
- New arguments are nda, hets, indelHeterozygosity, stand_call_conf, stand_emit_conf, ploidy, and maxAltAlleles
- Addresses PT 70110918
- To do this, moved those arguments out of the StandardCallerArgumentCollection into a new GenotypeCalculationArgumentCollection, which is now included as a member of SCAC
-They are now only computed when necessary
-Log10Cache is dynamically resizable, either by calling get() on an out-of-range value or by calling ensureCacheContains
-Log10FactorialCache and JacobianLogTable are initialized to a fixed size on first access and are not resizable
-Addresses PT 69124396
-Make BaseTest.createTempFile() mark any possible corresponding index files for deletion on exit
-Make WalkerTest mark shadow BCF files and auxiliary for deletion on exit
-Make VariantRecalibrationWalkersIntegrationTest mark PDF files for deletion on exit
-- disabling HC+VA integration test because, as noted in the comments, it keeps switching PairHMM implementations and giving different results at a particular site used in that particular test
Stories:
- https://www.pivotaltracker.com/story/show/69577868
Changes:
- Added a epsilon difference tolerance in weight comparisons.
Tests:
- Added HaplotypeCallerIntegrationTest#testDifferentIndelLocationsDueToSWExactDoubleComparisonsFix
- Updated md5 due to minor likelihood changes.
- Disabled a test for PathUtils.calculateCigar since does not work and is unclear what is causing the error (needs original author input)
To reduce merge conflicts, this commit modifies contents of files, while file renamings are in previous commit.
See previous commit message for list of changes.
To reduce merge conflicts, this commit only renames files, while file modifications are in next commit.
Some updates/fixes here are actually included in the next commit.
= Maven updates
Moved artifacts to new package names:
* private/queue-private -> private/gatk-queue-private
* private/gatk-private -> private/gatk-tools-private
* public/gatk-package -> protected/gatk-package-distribution
* public/queue-package -> protected/gatk-queue-package-distribution
* protected/gatk-protected -> protected/gatk-tools-protected
* public/queue-framework -> public/gatk-queue
* public/gatk-framework -> public/gatk-tools-public
New poms for new artifacts and packages:
* private/gatk-package-internal
* private/gatk-queue-package-internal
* private/gatk-queue-extensions-internal
* protected/gatk-queue-extensions-distribution
* public/gatk-engine
Updated references to StingText.properties to GATKText.properties.
Updated ant-bridge.sh to use gatk.* properties instead of sting.*.
= Engine updates
Renaming files containing engine parts from o.b.gatk.tools to o.b.gatk.engine.
Changed package references from tools to engine for CommandLineGATK, GenomeAnalysisEngine, ReadMetrics, ReadProperties, and WalkerManager.
Changed package reference tools.phonehome to engine.phonehome.
Renamed classes *Sting* to *GATK*, such as ReviewedGATKException.
= Test updates
Moved gatk example resources.
Moved test engine files from tools to engine packages.
Moved resources for phonehome to proper package.
Moved test classes under o.b.gatk into packages:
* o.b.g.utils.{BaseTest,ExampleToCopyUnitTest,GATKTextReporter,MD5DB,MD5Mismatch,TestNGTestTransformer}
* o.b.g.engine.walkers.WalkerTest
Updated package names in DependencyAnalyzerOutputLoaderUnitTest's data.
= Queue updates
Moving queue scripts to location where generated extensions can be used.
Renamed *.q to *.scala, updating licenses previously missed by git hooks.
Moved queue extensions to new artifact gatk-queue-extensions.
Fixed import statments frequently merge-conflicting on FullProcessingPipeline.scala.
= BWA
Added README on how to obtain and include bwa as a library.
Updated libbwa build.
Fixed packaged names under bwa/java implementation.
Updated contents of BWCAligner native implementation.
= Other fixes
Don't duplicate the resource bundle entries by both unpacking *and* appending.
(partial fix) Staged engine and utils poms to build GATKText.properties, once Utils random generator dependency on GATK engine is fixed.
Re-enabled custom testng listeners/reporters and moved testng dependencies to the gatk-root.
Updated comments referencing Sting with GATK.
Moved a couple untangled classes from gatk-tools-public to gatk-utils and gatk-engine.
The JNI treats shared memory as critical memory and doesn't allow any
parallel reads or writes to it until the native code finishes. This is
not a problem *per se* it is the right thing to do, but we need to
enable **-nct** when running the haplotype caller and with it have
multiple native PairHMM running for each map call.
Move to a copy based memory sharing where the JNI simply copies the
memory over to C++ and then has no blocked critical memory when running,
allowing -nct to work.
This version is slightly (almost unnoticeably) slower with -nct 1, but
scales better with -nct 2-4 (we haven't tested anything beyond that
because we know the GATK falls apart with higher levels of parallelism
* Make VECTOR_LOGLESS_CACHING the default implementation for PairHMM.
* Changed version number in pom.xml under public/VectorPairHMM
* VectorPairHMM can now be compiled using gcc 4.8.x
* Modified define-* to get rid of gcc warnings for extra tokens after #undefs
* Added a Linux kernel version check for AVX - gcc's __builtin_cpu_supports function does not check whether the kernel supports AVX or not.
* Updated PairHMM profiling code to update and print numbers only in single-thread mode
* Edited README.md, pom.xml and Makefile for users to pass path to gcc 4.8.x if necessary
* Moved all cpuid inline assembly to single function Changed info message to clog from cinfo
* Modified version in pom.xml in VectorPairHMM from 3.1 to 3.2
* Deleted some unnecessary code
* Modified C++ sandbox to print per interval timing
Story:
https://www.pivotaltracker.com/story/show/68220438
Changes:
- PL-less input genotypes are now uncalled and so non-variant sites when combining GVCFs.
- HC GVCF/BP_RESOLUTION Mode now outputs non-variant sites in sites covered by deletions.
- Fixed existing tests
Test:
- HaplotypeCallerGVCFIntegrationTest
- ReferenceConfidenceModelUnitTest
- CombineGVCFsIntegrationTest
story:
https://www.pivotaltracker.com/story/show/69648104
description:
This read transformer will refactor cigar strings that contain N-D-N elements to one N element (with total length of the three refactored elements).
This is intended primarily for users of RNA-Seq data handling programs such as TopHat2.
Currently we consider that the internal N-D-N motif is illegal and we error out when we encounter it. By refactoring the cigar string of
those specific reads, users of TopHat and other tools can circumvent this problem without affecting the rest of their dataset.
edit: address review comments - change the tool's name and change the tool to be a readTransformer instead of read filter
CalculateGenotypePosteriors now only computes posterior probs for SNP sites with SNP priors
(other sites have flat priors applied)
CalibrateGenotypeLikelihoods had originally applied HOM_REF/HET/HOM_VAR frequencies in callset as priors before empirical quality analysis. Now has option (-noPriors) to not apply/apply flat priors. Also takes in new external probabilities files, such as those generated by CGP, from which the genotype posterior probability qualities will be read.
Integration test was changed to account for new SNP-only behavior and default behavior to not use missing priors.
(Also, new numRefIfMissing is 0, which should only matter in cases using few samples when you probably don't want to be doing that anyway!)
Description:
Transforms a delegation dependency from HC to UG genotyping engine into a reusage by inhertance where HC and UG engines inherit from a common superclass GenotyperEngine
that implements the common parts. A side-effect some of the code is now more clear and redundant code has been removed.
Changes have a few consequence for the end user. HC has now a few more user arguments, those that control the functionality that HC was borrowing directly from UGE.
Added -ploidy argument although it is contraint to be 2 for now.
Added -out_mode EMIT_ALL_SITES|EMIT_VARIANTS_ONLY ...
Added -allSitePLs flag.
Stories:
https://www.pivotaltracker.com/story/show/68017394
Changes:
- Moved (HC's) GenotyperEngine to HaplotypeCallerGenotyperEngine (HCGE). Then created a engine superclass class GenotypingEngine (GE) that contains common parts between HCGE and the UG counterpart 'UnifiedGenotypingEngine' (UGE). Simplified the code and applied the template pattern to accomodate for small diferences in behaviour between both caller
engines. (There is still room for improvement though).
- Moved inner classes and enums to top-level components for various reasons including making them shorter and simpler names to refer to them.
- Create a HomoSpiens class for Human specific constants; even if they are good default for most users we need to clearly identify the human assumption across the code if we want to make
GATK work with any species in general; i.e. any reference to HomoSapiens, except as a default value for a user argument, should smell.
- Fixed a bug deep in the genotyping calculation we were taking on fixed values for snp and indel heterozygisity to be the default for Human ignoring user arguments.
- GenotypingLikehooldCalculationCModel.Model to Gen.*Like.*Calc.*Model.Name; not a definitive solution though as names are used often in conditionals that perhaps should be member methods of the
GenLikeCalc classes.
- Renamed LikelihoodCalculationEngine to ReadLikelihoodCalculationEngine to distinguish them clearly from Genotype likelihood calculation engines.
- Changed copy by explicity argument listing to a clone/reflexion solution for casting between genotypers argument collection classes.
- Created GenotypeGivenAllelesUtils to collect methods needed nearly exclusively by the GGA mode.
Tests :
- StandardCallerArgumentCollectionUnitTest (check copy by cloning/reflexion).
- All existing integration and unit tests for modified classes.
Following reviewers comments the command line interface has been simplified.
All extra strict validations are performed by default (as before) and the
user has to indicate which one he/she does not want to use with --validationTypeToExclude.
Before he/she was able to indicate the only ones to apply with --validationType but that has been scrapped out.
Stories:
- https://www.pivotaltracker.com/story/show/68725164
Changes:
- Removed validateType argument.
- Improved documentation.
- Added some warnning log message on suspicious argument combinations.
Tests:
- ValidateVariantsIntegrationTest#*
-- This is needed so the ref model pipeline can cut down to sites-only files without losing these useful statistics.
-- Added new unit test to test this info field annotation.
-- GenotypeGVCF integration tests change because new annotations are present in the output
More concretelly Picard's strict VCF validation does not like that there is alternative alleles that are not participating in any genotype call across samples.
This is an issue with GVCF in the single-sample pipeline where this is certainly expected with <NON_REF> and other relative unlikely alleles.
To solve this issue we allow the user to exclude some of the strict validations using a new argument --validationTypeToExclude. In order to avoid the validation
issue with GVCF the user needs to add the following to the command line: '--validationTypeToExclude ALLELES'
Story:
https://www.pivotaltracker.com/story/show/68725164
Changes:
- Added validateTypeToExclude argument to ValidateVariants walker.
- Implemented the selective exclusion of validation types.
- Added new info and improved existing documentation of the ValidateVariants walker.
Tests:
- ValidateVariantsIntegrationTest#testUnusedAlleleError
- ValidateVariantsIntegrationTest#testUnusedAlleleFix
In some cases, the program records were being removed from the BAM headers by the GATK engine
before we applied the check for reduced reads (so we did not fail appropriately). Pushed up the
check to happen before the PG tags are modified and added a unit test to ensure it stays that way.
It turns out that some UG tests still used reduced bams so I switched to use different ones.
Based on reviewer feedback, made it more generic so that it's easy to add new unsupported tools.
Previously it required you to create a single sample VCF and then to pass that in to the tool, but
Geraldine convinced me that this was a pain for users (because they usually have multi-sample VCFs).
Instead now you can pass in a multi-sample VCF and specify which sample's genotypes should be used
for the IUPAC encoding. Therefore the argument changed from '--useIUPAC' to '--use_IUPAC_sample NA12878'.
Stories:
https://www.pivotaltracker.com/story/show/66263868
Bug:
The problem was due to the way we were calculating the fix penalty of a large deletion or insertion. In this case we calculate the alignment likelihood of the portion
or read or haplotype deletion as the penalty of that deletion/insertion without going through the full pair-hmm process. For large events this resulted in a 0 in
in linear scale computations that ins transformed into an infinity in log scale.
Changes:
- Change to use log10 scale for calculate those penalties.
- Minor addition of .gitignore to hide ./public/external-example/target which is generated by the building process.
- SamPairUtils migrated in Picard r1737
- Revert IndelRealigner changes made in commit 4f4b85
-- Those changes were based on Picard revision 1722 to net/sf/picard/sam/SamPairUtil.java
-- Picard revision 1723 reverts these changes, so we also revert to match
Story:
- https://www.pivotaltracker.com/story/show/67601310
Change:
- Unless recover-danging-heads is active, the threading starting location policy is the original one. i.e. just at already existing unique kmer vertices.
Tests:
- HaplotypeCallerIntegrationTest#testMissingKeyAlternativeHaplotypesBugFix
1. Enable on-the-fly indexing for vcf.gz.
2. Handle on-the-fly indexing where file to be indexed is not a regular file, thus index should not be created.
3. Add method setProgressLogger to all SAMFileWriter implementations.
4. Revved picard to 1.109.1722
5. IndelRealigner md5s change because the MC tag is added to records now.
Fixed up and signed off by ebanks.
Currently the best haplotypes are those that accumulate the largest ABSOLUTE edge *multiplicity* sum across their path in the assembly graph.
The edge *mulitplicity* is equal to the number of reads that expand through that edge, i.e. have a kmer that uniquely map to some vertex up-stream from the edge and the following base calls extend across that edge to vertices downstream from it.
Despite that it is obvious that higher multiplicties correlated with haplotype probability this criterion fails short in some regards of which the most relevant is:
As it is evaluated in condensed seq-graph (as supposed to uncompressed read-threading-graphs) it is bias to haplotypes that have more short-sequence vetices
( -> ATGC -> CA -> has worse score than -> A -> T -> G -> C -> C -> A ->). This is partly result of how we modify the edge multiplicities when we merge vertices from a linear chain.
This pull-request addresses the problem by changing to a new scoring schema based in likelihood estimates:
Each haplotype's likelihood can be calculated as the multiplication of the likelihood of "taking" its edges in the assembly graph. The likelihood of "taking" an edge in the assembly
graph is calculated as its multiplicity divide by the sum of multiplicity of edges that share the same source vertex.
This pull-request addresses the following stories:
https://www.pivotaltracker.com/story/show/66691418https://www.pivotaltracker.com/story/show/64319760
Change Summary:
1. Change to the new scoring schema.
2. Added a graph DOT printing code to KBestHaplotypeFinder in order to diagnose scoring.
3. Graph transformation have been modified in order to generate no 0-multiplicity edges. (Nevertheless the schema above should work with 0 edges assuming that they are in fact 0.5)
Enable it with the new --useIUPAC argument.
Added both unit and integration tests for the new functionality - and fixed up the
exising tests once I was in there.
-- All the provided alleles are added to the assembly graph as potential haplotypes but they aren't forcibly genotyped like in GGA mode.
-- Added integration test for this mode
-These tests are really integration tests for Queue rather than generalized
pipeline tests, so it makes sense to call them QueueTests.
-Rename test classes and maven build targets, and update shell scripts
to reflect new naming.
C++ code has PAPI calls for reading hardware counters
Followed Khalid's suggestion for packing libVectorLoglessCaching into
the jar file with Maven
Native library part of git repo
1. Renamed directory structure from public/c++/VectorPairHMM to
public/VectorPairHMM/src/main/c++ as per Khalid's suggestion
2. Use java.home in public/VectorPairHMM/pom.xml to pass environment
variable JRE_HOME to the make process. This is needed because the
Makefile needs to compile JNI code with the flag -I<JRE_HOME>/../include (among
others). Assuming that the Maven build process uses a JDK (and not just
a JRE), the variable java.home points to the JRE inside maven.
3. Dropped all pretense at cross-platform compatibility. Removed Mac
profile from pom.xml for VectorPairHMM
Moved JNI_README
1. Added the catch UnsatisfiedLinkError exception in
PairHMMLikelihoodCalculationEngine.java to fall back to LOGLESS_CACHING
in case the native library could not be loaded. Made
VECTOR_LOGLESS_CACHING as the default implementation.
2. Updated the README with Mauricio's comments
3. baseline.cc is used within the library - if the machine supports
neither AVX nor SSE4.1, the native library falls back to un-vectorized
C++ in baseline.cc.
4. pairhmm-1-base.cc: This is not part of the library, but is being
heavily used for debugging/profiling. Can I request that we keep it
there for now? In the next release, we can delete it from the
repository.
5. I agree with Mauricio about the ifdefs. I am sure you already know,
but just to reassure you the debug code is not compiled into the library
(because of the ifdefs) and will not affect performance.
1. Changed logger.info to logger.warn in PairHMMLikelihoodCalculationEngine.java
2. Committing the right set of files after rebase
Added public license text to all C++ files
Added license to Makefile
Add package info to Sandbox.java
Conflicts:
protected/gatk-protected/src/main/java/org/broadinstitute/sting/gatk/walkers/haplotypecaller/HaplotypeCaller.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/gatk/walkers/haplotypecaller/PairHMMLikelihoodCalculationEngine.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/utils/pairhmm/DebugJNILoglessPairHMM.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/utils/pairhmm/JNILoglessPairHMM.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/utils/pairhmm/VectorLoglessPairHMM.java
public/VectorPairHMM/src/main/c++/.gitignore
public/VectorPairHMM/src/main/c++/LoadTimeInitializer.cc
public/VectorPairHMM/src/main/c++/LoadTimeInitializer.h
public/VectorPairHMM/src/main/c++/Makefile
public/VectorPairHMM/src/main/c++/Sandbox.cc
public/VectorPairHMM/src/main/c++/Sandbox.h
public/VectorPairHMM/src/main/c++/Sandbox.java
public/VectorPairHMM/src/main/c++/Sandbox_JNIHaplotypeDataHolderClass.h
public/VectorPairHMM/src/main/c++/Sandbox_JNIReadDataHolderClass.h
public/VectorPairHMM/src/main/c++/baseline.cc
public/VectorPairHMM/src/main/c++/define-double.h
public/VectorPairHMM/src/main/c++/define-float.h
public/VectorPairHMM/src/main/c++/define-sse-double.h
public/VectorPairHMM/src/main/c++/define-sse-float.h
public/VectorPairHMM/src/main/c++/headers.h
public/VectorPairHMM/src/main/c++/jnidebug.h
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_DebugJNILoglessPairHMM.cc
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_DebugJNILoglessPairHMM.h
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_VectorLoglessPairHMM.cc
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_VectorLoglessPairHMM.h
public/VectorPairHMM/src/main/c++/pairhmm-template-kernel.cc
public/VectorPairHMM/src/main/c++/pairhmm-template-main.cc
public/VectorPairHMM/src/main/c++/run.sh
public/VectorPairHMM/src/main/c++/shift_template.c
public/VectorPairHMM/src/main/c++/utils.cc
public/VectorPairHMM/src/main/c++/utils.h
public/VectorPairHMM/src/main/c++/vector_function_prototypes.h
-- throws UserException; added tests in PosteriorLikelihoodsUtilsUnitTests
Add error handling to CalculateGenotypePosteriors for cases where MLEAC>AN; add tests in PosteriorLikelihoodsUtilsUnitTests
Add unit tests to confirm that CalculateGenotypePosteriors has the ability to switch genotypes for four cases
Phillip Dexheimer
Laura Gauthier
Ryan Poplin
Valentin Ruano-Rubio
Ron Levine
Geraldine Van der Auwera
Ron Levine
Menachem Fromer
Khalid Shakir
Sheila Chandran
Ron Levine
Eric Banks
droazen
Tim Fennell
EvolvedMicrobe
Nigel Delaney
Karthik Gururaj
MauricioCarneiro
Ami Levy-Moonshine
Kristian Cibulskis
Joel Thibault
Alec Wysoker
Bertrand Haas