- Added RR qual correctness tests (note that this is a case where we don't add code coverage but still need to test critical infrastructure).
- Also added minor cleanup of BaseUtils
I've confirmed via a script that all of these differences only
involve the version number bump in the BAM headers and nothing
else:
< @HD VN:1.0 GO:none SO:coordinate
---
> @HD VN:1.4 GO:none SO:coordinate
testing the adding of reads into the SlidingWindow plus consensus creation. Will flesh these out more after I take care of
some other items on my plate.
-- All functions tested. In the testing / review I discovered several bugs in the ActiveRegion routines that manipulate reads. New version should be correct
-- Enforce correct ordering of supporting states in constructor
-- Enforce read ordering when adding reads to an active region in add
-- Fix bug in HaplotypeCaller map with new updating read spans. Now get the full span before clipping down reads in map, so that variants are correctly placed w.r.t. the full reference sequence
-- Encapsulate isActive field with an accessor function
-- Make sure that all state lists are unmodifiable, and that the docs are clear about this
-- ActiveRegion equalsExceptReads is for testing only, so make it package protected
-- ActiveRegion.hardClipToRegion must resort reads as they can become out of order
-- Previous version of HC clipped reads but, due to clipping, these reads could no longer overlap the active region. The old version of HC kept these reads, while the enforced contracts on the ActiveRegion detected this was a problem and those reads are removed. Has a minor impact on PLs and RankSumTest values
-- Updating HaplotypeCaller MD5s to reflect changes to ActiveRegions read inclusion policy
Please check that your commit hook is properly pointing at ../../private/shell/pre-commit
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
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)...
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
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
-- Added HCPerformance evaluation Qscript
-- Added some docs about one of the HC integration tests
-- HaplotypeCaller / ART performance evaluation script
- Added an optional argument to BaseRecalibrator to produce sorted GATKReport Tables
- Modified BSQR Integration Tests to include the optional argument. Tests now produce sorted tables
The weird part is that the comments claimed it was doing what it was supposed to, but it didn't actually do it.
Now we maintain the last header element of the consensus (but without bases and quals) if it adjoins an element with an insertion.
Added the user's test file as an integration test.
This is an intermediate commit so that there is a record of these changes in our
commit history. Next step is to isolate the test classes as well, and then move
the entire package to the Picard repository and replace it with a jar in our repo.
-Removed all dependencies on org.broadinstitute.sting (still need to do the test classes,
though)
-Had to split some of the utility classes into "GATK-specific" vs generic methods
(eg., GATKVCFUtils vs. VCFUtils)
-Placement of some methods and choice of exception classes to replace the StingExceptions
and UserExceptions may need to be tweaked until everyone is happy, but this can be
done after the move.
Reads that are soft-clipped off the contig (before the beginning of the contig) were being soft-clipped to position 0 instead of 1 because of an off-by-one issue. Fixed and included in the integration test.
-- Uses high-performance local writer backed by byte array that writes the entire VCF line in some write operation to the underlying output stream.
-- Fixes problems with indexing of unflushed writes while still allowing efficient block zipping
-- Same (or better) IO performance as previous implementation
-- IndexingVariantContextWriter now properly closes the underlying output stream when it's closed
-- Updated compressed VCF output file
-Switch back to the old implementation, if needed, with --use_legacy_downsampler
-LocusIteratorByStateExperimental becomes the new LocusIteratorByState, and
the original LocusIteratorByState becomes LegacyLocusIteratorByState
-Similarly, the ExperimentalReadShardBalancer becomes the new ReadShardBalancer,
with the old one renamed to LegacyReadShardBalancer
-Performance improvements: locus traversals used to be 20% slower in the new
downsampling implementation, now they are roughly the same speed.
-Tests show a very high level of concordance with UG calls from the previous
implementation, with some new calls and edge cases that still require more examination.
-With the new implementation, can now use -dcov with ReadWalkers to set a limit
on the max # of reads per alignment start position per sample. Appropriate value
for ReadWalker dcov may be in the single digits for some tools, but this too
requires more investigation.
As reported by Menachem Fromer: a critical bug in AFCalcResult:
Specifically, the implementation:
public boolean isPolymorphic(final Allele allele, final double log10minPNonRef) {
return getLog10PosteriorOfAFGt0ForAllele(allele) >= log10minPNonRef;
}
seems incorrect and should probably be:
getLog10PosteriorOfAFEq0ForAllele(allele) <= log10minPNonRef
The issue here is that the 30 represents a Phred-scaled probability of *error* and it's currently being compared to a log probability of *non-error*.
Instead, we need to require that our probability of error be less than the error threshold.
This bug has only a minor impact on the calls -- hardly any sites change -- which is good. But the inverted logic effects multi-allelic sites significantly. Basically you only hit this logic with multiple alleles, and in that case it'\s including extra alt alleles incorrectly, and throwing out good ones.
Change was to create a new function that properly handles thresholds that are PhredScaled quality scores:
/**
* Same as #isPolymorphic but takes a phred-scaled quality score as input
*/
public boolean isPolymorphicPhredScaledQual(final Allele allele, final double minPNonRefPhredScaledQual) {
if ( minPNonRefPhredScaledQual < 0 ) throw new IllegalArgumentException("phredScaledQual " + minPNonRefPhredScaledQual + " < 0 ");
final double log10Threshold = Math.log10(QualityUtils.qualToProb(minPNonRefPhredScaledQual));
return isPolymorphic(allele, log10Threshold);
}
Guillermo del Angel
Eric Banks
Ryan Poplin
David Roazen
Mark DePristo
Mauricio Carneiro
Ami Levy-Moonshine
Chris Hartl
Tad Jordan