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Conflicts:
public/java/test/org/broadinstitute/variant/VariantBaseTest.java
-Moved some of the more specialized / complex VariantContext and VCF utility
methods back to the GATK.
-Due to this re-shuffling, was able to return things like the Pair class back
to the GATK as well.
One of the fixes was critical: SlidingWindow was not converting between global and relative positions correctly.
Besides not being correct, it was resulting in a massive slow down of the RR traversal.
That fix definitely breaks at least one of the integration tests, but it's not worth changing md5s now because I'll be
changing things all over RR for the next few days, so I am going to let that test fail indefinitely until I can confirm
general correctness of the tool.
a) Add option to stratify CalibrateGenotypeLikelihoods by repeat - will add integration test in next push.
b) Simulator to produce BAM files with given error profile - for now only given SNP/indel error rate can be given. A bad context can be specified and if such context is present then error rate is increased to given value.
c) Rewrote RepeatLength covariate to do the right thing - not fully working yet, work in progress.
d) Additional experimental covariates to log repeat unit and combined repeat unit+length. Needs code refactoring/testing
-- Allows us to avoid doing a lot of misc. work to set up the genotype when we don't have any data to genotype. Valuable in the case where we are passing through large regions without any data
-- This new algorithm is essential to properly handle activity profiles that have many large active regions generated from lots of dense variant events. The new algorithm passes unit tests and passes visualize visual inspection of both running on 1000G and NA12878
-- Misc. commenting of the code
-- Updated ActiveRegionExtension to include a min active region size
-- Renamed ActiveRegionExtension to ActiveRegionTraversalParameters, as it carries more than just the traversal extension now
-- Required before I jump in an redo the entire activity profile so it's can be run imcrementally
-- This restructuring makes the differences between the two functionalities clearer, as almost all of the functionality is in the base class. The only functionality provided by the BandPassActivityProfile is isolated to a finalizeProfile function overloaded from the base class.
-- Renamed ActivityProfileResult to ActivityProfileState, as this is a clearer indication of its actual functionality. Almost all of the misc. walker changes are due to this name update
-- Code cleanup and docs for TraverseActiveRegions
-- Expanded unit tests for ActivityProfile and ActivityProfileState
Testing for moltenized output, and for genotype-level filtering. This tool is now fully functional. There are three todo items:
1) Docs
2) An additional output table that gives concordance proportions normalized by records in both eval and comp (not just total in eval or total in comp)
3) Code cleanup for table creation (putting a table together the way I do takes -way- too many lines of code)
2. While making the previous fix and unifying FS for SNPs and indels, I noticed that FS was slightly broken in the general case for indels too; fixed.
3. I also fixed a minor bug in the Allele Biased Downsampling code for reduced reads.
I've resigned myself instead to create a mapping from Allele to Haplotype. It's cheap so not a big deal, but really shouldn't be necessary.
Ryan and I are talking about refactoring for GATK2.5.
-- UnitTests now include combinational tiling of reads within and spanning shard boundaries
-- ART now properly handles shard transitions, and does so efficiently without requiring hash sets or other collections of reads
-- Updating HC and CountReadsInActiveRegions integration tests
Out of curiosity, why does Picard's IndexedFastaSequenceFile allow one to query for start position 0? When doing so, that base is a line feed (-1 offset to the first base in the contig) which is an illegal base (and which caused me no end of trouble)...
Refactored interval specific arguments out of GATKArgumentCollection into InvtervalArgumentCollection such that it can be used in other CommandLinePrograms.
Updated SelectHeaders to print out full interval arguments.
Added RemoteFile.createUrl(Date expiration) to enable creation of presigned URLs for download over http: or file:.
This way walkers won't see anything except the standard bases plus Ns in the reference.
Added option to turn off this feature (to maintain backwards compatibility).
As part of this commit I cleaned up the BaseUtils code by adding a Base enum and removing all of the static indexes for
each of the bases. This uncovered a bug in the way the DepthOfCoverage walker counts deletions (it was counting Ns instead!) that isn't covered by tests. Fortunately that walker is being deprecated soon...
Completed todo item: for sites like
(eval)
20 12345 A C
20 12345 A AC
(comp)
20 12345 A C
20 12345 A ACCC
the records will be matched by the presence of a non-empty intersection of alleles. Any leftover records are then paired with an empty variant context (as though the call was unique). This has one somewhat counterintuitive feature, which is that normally
(eval)
20 12345 A AC
(comp)
20 12345 A ACCC
would be classified as 'ALLELES_DO_NOT_MATCH' (and not counted in genotype tables), in the presence of the SNP, they're counted as EVAL_ONLY and TRUTH_ONLY respectively.
+ integration test
This way, we don't need to create a new Allele for every read/Haplotype pair to be placed in the PerReadAlleleLikelihoodMap (very inefficient). Also, now we can easily get the Haplotype associated with the best allele for a given read.
2. Framework is set up in the VariantAnnotator for the HaplotypeCaller to be able to call in to annotate dbSNP plus comp RODs. Until the HC uses meta data though, this won't work.
-- Resolved what was clearly a bug in UG (GGA mode was returning a neighboring, equivalent indel site that wasn't in input list. Not ideal)
-- Trivial read count differences in HC
-- function to create pileup elements in AlignmentStateMachine and LIBS
-- Cleanup pileup element constructors, directing users to LIBS.createPileupFromRead() that really does the right thing
-- Optimizations to AlignmentStateMachine
-- Properly count deletions. Added unit test for counting routines
-- AlignmentStateMachine.java is no longer recursive
-- Traversals now use new LIBS, not the old one
-- Added HCPerformance evaluation Qscript
-- Added some docs about one of the HC integration tests
-- HaplotypeCaller / ART performance evaluation script
Instead of the GATK Engine creating a new BaseRecalibrator (not clean), it just keeps track of the arguments (clean).
There are still some dependency issues, but it looks like they are related to Ami's code. Need to look into it further.
Mauricio Carneiro
David Roazen
Eric Banks
Ryan Poplin
Guillermo del Angel
Mark DePristo
Ami Levy-Moonshine
Chris Hartl
Khalid Shakir