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!)
The new tool gets an VCF file as an input and create a GATK report with the percentages of each mutation type (e.g. A->G, A->T...).
It allow the user to filter sites that will be count based of JXEL or based on the varait quals
A user can aslo print 12 VCF files (one for each mutation) with the VCF line of the mutations that were counted.
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.
-- We no longer use QUAL because it scales insidiously with AC.
-- By default we exclude sites in which NA12878 is polymorphic to prevent overfitting to the knowledgebase.
-- Tweaks to training parameters were required because of the QUAL change.
-- We now test for model convergence instead of specifying the number of iterations at the command line.
Laura Gauthier
MauricioCarneiro
Karthik Gururaj
Ryan Poplin
Valentin Ruano-Rubio
jmthibault79
Michael McCowan
kshakir
Carlos Borroto
Ami Levy-Moonshine
Eric Banks
droazen
Kristian Cibulskis
Khalid Shakir
Mike