This syntax predates the ability to have multiple -L arguments, is
inconsistent with the syntax of all other GATK arguments, requires
quoting to avoid interpretation by the shell, and was causing
problems in Queue.
A UserException is now thrown if someone tries to use this syntax.
-- Now you provide a LazyParsing object
-- LazyGenotypesContext now knows nothing about the VCF parser itself. The parser holds all of the necessary data to parse the VCF genotypes when necessarily, and the LGC only has a pointer to this object
-- Using new interface added LazyGenotypesContext to unit tests with a simple lazy version
-- Deleted VCFParser interface, as it was no longer necessary
-- With our GenotypesContext class we can naturally create a LazyGenotypesContext subclass that does the on-demand loading.
-- This new class was replaced all of the old, complex functionality
-- Better still, there were many cases were the genotypes were being loaded unnecessarily, resulting in efficiency. This was detected because some of the integration tests changed as the genotypes were no longer being parsing unnecessarily
-- Misc. bug fixes throughout the system
-- Bug fixes for PhaseByTransmission with new GenotypesContext
-- We should no longer have md5s changing because of hashmaps changing their sort order on us
-- Added GenotypeLikelihoodsUnitTests
-- Refactored ExactAFCaclculation to put the PL -> QUAL calculation in the GenotypeLikelihoods class to avoid the code copy.
-- New approach to making VariantContexts modeled on StringBuilder
-- No more modify routines -- use VariantContextBuilder
-- Renamed isPolymorphic to isPolymorphicInSamples. Same for mono
-- getChromosomeCount -> getCalledChrCount
-- Walkers changed to use new VariantContext. Some deprecated new VariantContext calls remain
-- VCFCodec now uses optimized cached information to create GenotypesContext.
-- Major change to how chromosomeCounts is computed. Now NO_CALL alleles are always excluded. So ChromosomeCounts(A/.) is 1, the previous result would have been 2.
-- Naming changes for getSamplesNameInOrder()
-- Now these routines all iterate in sample name order (genotypes.iterateInSampleNameOrder) so that the results of UG and the annotator do not depend on the particular order of samples we see for the exact model and the RankSumTest
-Modified the SnpEff parser to work with the SnpEff 2.0.4 VCF output format
-Assigning functional classes and effect impacts now handled directly
by SnpEff rather than the GATK
-Removed support for SnpEff 2.0.2, as we no longer trust the output of that
version since it doesn't exclude effects associated with certain nonsensical
transcripts. These effects are excluded as of 2.0.4.
-Updated unit and integration tests
This support is based on a *release-candidate* of SnpEff 2.0.4, and so is subject
to change between now and the next GATK release.
compressed the representation of the reduce reads counts by offset results in 17% average compression in final BAM file size.
Example compression -->
from : 10, 10, 11, 11, 12, 12, 12, 11, 10
to: 10, 0, 1, 1,2, 2, 2, 1, 0
-- I have no idea why I named this InferredGeneticContext, a totally meaningless term
-- Renamed to CommonInfo.
-- Made package protected, as no one should use this outside of VariantContext and Genotype
-- UGEngine was using IGC constant, but it's now using the public one in VariantContext.
-- Enables further sophisticated optimizations, as this class can be smarter about storing the data and will directly support operations like subset to samples
-- All instances in the gatk that used Map<String, Genotype> now use GenotypeMap type.
-- Amazingly, there were many places where HashMap<String, Genotype> is used, so that the order of the genotypes is technically undefined and could be dangerous. Now everything uses GenotypeMap with a specific ordering of samples (by name)
-- Integrationtests updated and all pass
-- This is a more convenient accesssor than subContextOfGenotypes, represents nearly all of the use cases of the former function, and potentially can be implemented more efficiently.
The primary use of this stratification is to provide a mechanism to divide asssessment of a call set up by whether a variant overlaps an interval or not. I use this to differentiate between variants occurring in CCDS exons vs. those in non-coding regions, in the 1000G call set, using a command line that looks like:
-T VariantEval -R human_g1k_v37.fasta -eval 1000G.vcf -stratIntervals:BED ccds.bed -ST IntervalStratification
Note that the overlap algorithm properly handles symbolic alleles with an INFO field END value. In order to safely use this module you should provide entire contigs worth of variants, and let the interval strat decide overlap, as opposed to using -L which will not properly work with symbolic variants.
Minor improvements to create() interval in GenomeLocParser.
* Generalized the concept of a synthetic read to cread both running consensus and a synthetic reads of filtered data.
* Synthetic reads can now have deletions (but not insertions)
* New reduced read tag for filtered data synthetic reads *(RF)*
* Sliding window header now keeps information of consensus and filtered data
* Synthetic reads are created simultaneously, new functionality is controlled internally by addToSyntheticReads
-- A bit of code cleanup in VCFUtils
-- VariantEval table to create 1000G Phase I variant summary table
-- First version of 1000G Phase I summary table Qscript
Table codec now yells at users for not providing a HEADER with the table - parsing tables without a header line was causing the first line of the file to be eaten.
Table feature now has a toString method.
These are minor bug fixes.
when constructing a GATKSAMRecord from scratch, we should set "mRestOfBinaryData" to null so the BAMRecord doesn't try to retrieve missing information from the non-existent bam file.
-- vcfWriter2 was never being closed in onTraversalDone(), so the on the fly index file was being created but never actually properly written to the file.
-- This bug is ultimately due to the inability of the GATK to allow multiple VCF output writers as @Output arguments, though
-- Removed the unnecessary local variable iFraction, = 1000 * the input fraction argument. Now the system just uses a double random number and compares to the input fraction at all. Is there some subtle reason I don't appreciate for this programming construct?
The GATK engine will now provide a GATKSAMRecord to all tools which incorporates the functionality used by the GATK to the bam file (ReadGroups, Reduced Reads, ...).
* No tools should create SAMRecord anymore, use GATKSAMRecord instead *
-- scatterLocusIntervals master utility
-- Moved around some general functionality from GenomeLocSortedSet to GenomeLoc
-- Util function for reversing a list (List<T> -> List<T>, unlike Collections version)
-- DoC is PartitionType.INTERVAL
-- Significant unit tests on new functionality (all passing)
-- Ready for real-world testing, as soon as I can get LocusScatterFunction.scala to actually work
Mark DePristo
Eric Banks
David Roazen
Mauricio Carneiro
Matt Hanna
Roger Zurawicki
Khalid Shakir
Laurent Francioli
Guillermo del Angel
Ryan Poplin
Christopher Hartl