The major effects of this commit are as follows:
1. We no longer skip any good bases (of course, this change alone breaks every single integration test).
2. The dinuc covariate returns a "no dinuc" value for the first base of a read (but not for the last base anymore, since there is a valid dinuc) or if the previous base is a bad base (e.g. 'N').
I've done a bunch of testing on real data and everything looks right; however, let's wait until the recalibrator guru gets back from vacation next week and can double-check everything before shipping this out in another early access release.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2443 348d0f76-0448-11de-a6fe-93d51630548a
Also updating other IntervalCleanerIntegrationTest failures that were masked by my first patch.
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1) sam-jdk apparently no longer supports custom tags with type int[] values.
2) BAM output for indel cleaner integration test changed in a way that's so subtle it can't be seen after converting the output to .sam.
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1: all overlapping and abutting intervals merged (ALL),
2: just overlapping, not abutting intervals (OVERLAPPING_ONLY),
3: no merging (NONE). This option is not currently allowed, it will throw an exception. Once we're more certain that unmerged lists are going to work in all cases in the GATK, we'll enable that.
The command line option is --interval_merging or -im
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1. allele balance annotation is now weighted by genotype quality (so we don't get misled by borderline het calls)
2. Updates to the Unified Genotyper for parallelization:
a. verbose writing now works again; arg was moved from UAC to UG
b. UG checks for command that don't work with parallelization
c. some cleanup
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The cycle covariate is now first/second of pair aware. I'm taking it on faith from both Chris Hartl (waiting on slides from him) and Tim that this is the right thing to do. We'll have Ryan confirm it all next week.
The only change is that if a read is the second of a pair, we multiple the cycle by -1 (a simple way of separating its index from that of its mate).
Of course, this broke all integration tests.
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Also, slightly optimized the cleaner by using readBases (instead of readString) and caching cigar element lengths.
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2. isNoCall() added to Genotype interface so that we can distinguish between ref and no calls (all we had before was isVariant())
3. Added Hardy-Weinberg annotation; still experimental - not working yet so don't use it.
4. Move 'output type' argument out of the UnifiedArgumentCollection and into the UnifiedGenotyper, in preparation for parallelization.
5. Improved some of the UG integration tests.
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Reworked all of the integration tests so that they're now more comprehensive, cover more of what we wan to test, and don't take forever to run.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2376 348d0f76-0448-11de-a6fe-93d51630548a
Bad/suspicious bases/reads (high mismatch rate, low MQ, low BQ, bad mates) are now filtered out by default (and not used for the annotations either), although this can all be turned off.
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[Also, enable Mark's new UG arguments]
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Modified - Hapmap now takes a -q command to filter out variants by quality
Modified - MathUtils - cumBinomialProbLog now uses BigDecimal to handle some numerical imprecisions
Modified - PowerBelowFrequency - returns 0.0 if called with a negative number (can't be done from inside the walker itself, but since it's called elsewhere one can't be too careful)
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1. Initial code for annotating calls with the base mismatch rate within a reference window (still needs analysis).
2. Move error checking code from rodVCF to VCFRecord.
3. More improvements to SNP Genotype callset concordance.
4. Fixed some comments in Variation/Genotype
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The only major difference is that we are now able to get accurate allele balance ratios.
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We could still use more, but this is a good start.
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- Hook up Variation and Genotype in SSG
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- Removed MQ0 annotation
- Updated RMS MQ annotation to use new pileup
- UG now outputs all of its arguments as key/value pairs in the header (for VCF)
- Cleaned up VCFGenotypeWriterAdapter interface a bit
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We are now VCF3.3 compliant.
(Only a few more stages left. Sigh.)
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VCFRecord now implements Variation, VCFGenotypeRecord now implements Genotype.
Because of this change, RodVCF is now just a wrapper around the VCFRecord and does nothing else. Also, one can call toVariation on the VCFGenotypeRecord and it returns the VCFRecord.
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This stage consists only of the code originating in the Genotyper and flowing through to the genotype writers. I haven't finished refactoring the writers and haven't even touched the readers at all.
The major changes here are that
1. Variations which are BackedByGenotypes are now correctly associated with those Genotypes
2. Genotypes which have an associated Variation can actually be associated with it (and then return it when toVariation() is called).
The only integration tests which need to be updated are MSG-related (because the refactoring now made it easy for me to prevent MSG from emitting tri-allelic sites).
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2. Fixed bug in histogram calculation for small intervals
3. Better output in DoCWalker
4. Comments added to code
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I am now at a point where I can merge the functionality from other coverage walkers into this one.
Thanks to Andrew for input.
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- Moved validation walkers to new qc dir
- Killed unused test
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- Renamed keys to fit with the standard naming
- FisherStrand is no longer standard
- Integration tests no longer test experimental annotations since they're not stable
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getNegLog10PError() does not equal the confidence score (you need to multiply by 10 as confidence is traditionally phred scaled). Probably we should change the method to be getNeg10Log10PError(). Anyone have strong feelings on this?
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- DepthOfCoverage is now by reference (so locus-by-locus output correctly reports zero-coverage bases)
- VariantsToVCF now lets you bind variants with any string except intervals and dbsnp (not just NA######)
- A PileupWalker integration test on a particularly nasty FHS site
- Two second-base annotation related integration tests on that same site
+ outputs were all hand-validated in matlab; within a certain tolerance for the annotations
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1. Only do calculations in UG for alternate allele with highest sum of quality scores (note that this also constitutes a bug fix for a precision problem we were having).
2. Avoid using Strings in DiploidGenotype when we can (it was taking 1.5% of my compute according to JProfiler)
UG now runs in half the time for JOINT_ESTIMATE model.
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Computes a metric for how much error is left that isn't explained by ref or snp bases. This is the sum of Q scores, weighted by the proportion of non-ref non-snp bases to non-snp bases. Reported in Log space.
Update to the integration test so bamboo doesn't look as though someone murdered it with a spork
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2124 348d0f76-0448-11de-a6fe-93d51630548a
Added integration test for pooled model and updated other joint estimation tests to be more comprehensive now that they are faster.
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2. Retired allele frequency range from UG, which wasn't very useful.
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[There was no reason to enforce that every VCF being output from the GATK should have the samples sorted, since someone might want them ordered non-alphabetically]
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Updated the integration tests that were failing to due to different ordering of genotyping entries in VCF, I'll check in the VCF diff tool I wrote when I get a cycle or two.
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2. Allele frequency spectrum is not emitted for single samples (since it doesn't make sense).
3. If in pooled mode, throw an exception of pool size isn't set appropriately.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2072 348d0f76-0448-11de-a6fe-93d51630548a
This will output for hapmap variant sites:
chromosome position ref allele variant allele number of variant alleles of the individuals depth of coverage power to detect singletons at lod 3 number of variant bases seen whether or not variant was called
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Second base skew annotations and integration tests. Nothing need be given except -A SecondBaseSkew; the statistic it annotates calls with is a chi-square statistic given by the deviation of the observed proportion of reference second-best-bases from the expected 1/3. Future additions may be to ask that the deviation be instead from a given transition table.
A big note for all users: All IllegalStateExceptions from the variation ROD (e.g. the RodGeliText) are dealt with SILENTLY. I understand this isn't optimal, but I'd rather simply not annotate a non-bi-allelic site than fail completely (there are quite a few such sites even on the regions over which the integration test has been written).
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