Unrelated change: in the sorted-target mode (when we read sorted target intervals one by on from a file), one can now specify multiple semicolon-separated interval files (all must be sorted). Not hugely useful probably, but makes --targetIntervals always process its values in exactly the same way, so we are consistent (it has been already taking ;-separated args in unsorted mode)
NwayIntervalMergingIterator: reads in multiple sorted GenomeLoc input streams (iterators) and presents them as a single sorted and merged stream
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interaction with Tribble. In Tribble, keeping these references in memory until
the shard is flushed means keeping one 512K character buffer per object in
memory. Fixed by purging the reference to the object at the end of the
shard traversal.
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of traversal to avoid holding a reference to the microscheduler, which holds a reference to
the engine, which in turn holds a reference to the walker, which itself holds a reference to
all the data aggregated during the course of the traversal.
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parsing engine. Hugely lowers our memory footprint in integrationtests, but not yet enough to
run Mark's new parallelized VariantEvalIntegrationTests.
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with -nt option. When last I checked in, Ryan was seeing a ~25% speedup
per shard by not indexing.
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with a more sensible strategy for sharding w/o BAMs at some point after
ASHG.
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a) Fix it up because it broke with a recent checkin to annotate vcf with unfiltered depth.
b) Printout of ref/alt alleles in output vcf was incorrect because the start/stop positions of associated GenomeLoc were incorrectly computed in case of a deletion.
c) Redid Beagle input/output walkers as not assume that ref was a single base, not to assume that variant was a vcf and generalized it to be indel-capable, so now the Beagle walkers can be used for indels as well.
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Modified - SelectVariants: Hook up to VariantContextUtils to recalculate AC/AF/AN, which uses the accessor in VariantContext to do this. Somehow sites that were selected down to hom-ref genotypes only wound up getting positive AC.
**IMPORTANT** I kind of need input here. The header of a file used for an integration test specifies AC as being an integer. Recalculating it casts it into an integer list (which it should be, as it allows for alternate alleles). However this appears to clash with what the jexl expression is looking for? For now, the integration test itself needed to be changed -- it's unclear what to do when the header specifies AC of being one class, but recalculating it casts to another class, and I'm not sure what to do.
I'm committing my omni_qc pipeline because I'm almost certain 2 months down the road I'm going to wonder what the heck I did to generate my results.
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1: -sample can now include a file, which will be parsed for sample-name entries
2: If you request a sample to run analysis on, but it is not present in any of your RODs, VEW will exception out
3: Change added to parse Integer, String, and List<Integer> type Allele Count annotations (error otherwise)
4 [slightly problematic]: The count objects now maintain row-keys in order, as the keys were taking an inordinate amount of time in onTraversalDone (multiple calls to getRowKeys(), so many multiple sorts of the same underlying unsorted object, very bad)
There is a legacy comparison object which is unused which I will strip out soon.
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The core walker has been modified so that when variant contexts (eval and comp) are subset to command-line-specified sample(s), the chromosome count annotations (AC/AN/AF) are altered to reflect the AC/AN/AF of only those samples involved in the comparison. No more getting AC500 when you're comparing a 10-sample overlap. Interestingly enough, this didn't break any integration tests.
GenotypeConcordance now has two additional tables: Allele Count Statistics, and Allele Count Summary Statistics. These work exactly identically to the Sample Statistics and Sample Summary Statistics tables, except that the partition being used is no longer the sample, but instead the allele count of the variant sites. These tables stratify by both eval and comp ACs, e.g.
evalAC0
evalAC1
evalAC2
compAC0
compAC1
compAC2
Differences with previous integration tests were verified to only be in the Allele Count tables (by grepping them out of the diff); a new test has been added for the simple case of an AC=1 site in the eval becoming an AC=2 site in the comp.
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that have 0 aligned bases in the genome. We'll have to fix walkers as faults
appear.
Also added JIRA GSA-406: finer-grained control of MalformedReadFilter: want
to exception out by default in these cases but pass them with a warning with
a corresponding -U flag.
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- ProduceBeagleInputWalker
+ Now takes a validation ROD and a prior to give it, will use those genotypes in place of the variant genotypes if both are present
+ Takes a bootstrap argument -- can use some given %age of the validation sites
+ Optionally takes a bootstrap output argument -- re-prints the validation VCF, filtering those sites used as part of the bootstrap
-BeagleOutputToVCFWalker
+ Now filters sites where the genotypes have been reverted to hom ref
+ Now calls in to the new VCUtils to calculate AC/AN
-Queue
+ New pipeline libraries for easy qscript creation, still a work in progress, but this is a considerable prototype
+ full calling pipeline v2 uses the above libraries
+ minor changes to some of my own scripts
+ no more need for contig interval lists, these will be parsed out of your normal interval list when it is provided
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Previous output spec contained 3 columns:
haplotypeReference,haplotypeAlternate,haplotypeStrand
where haplotypeReference was always on the + strand, and haplotypeAlternate was on the strand specified by haplotypeStrand.
The new specification contains 3 columns:
haplotypeReference,haplotypeAlternate,transcriptStrand
where haplotypeRef and haplotypeAlt are required to be on the + strand. transcriptStrand now specifies the strand of the transcript, which is needed for interpreting the haplotypes.
Bugfix #1: fix incorrect assignment of variantCodon and variantAA
(Previously variantCodon was incorrectly set to referenceCodon)
Bugfix #2: fix incorrect codingCoordStr values for - strands (bug reported by Giulio Genovese), and incorrect usage of "m." for mitochondrial transcripts (bug reported by Steve Hershman)
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Why v3, you ask? Why not? Simply because v2 was a String so old and clunky, the sun would fizzle out and grow cold before any VCF could be successfully parsed.
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Off to Yosemite in 4 hours, enjoy the week gsa folks!
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- Brought over exact AF estimation from branch (which is now dead). Exact model is default in UnifiedGenotyperV2.
- Implemented completely new genotyping algorithm given best AF estimate using dynamic programming, which in theory should be better than both greedy search and any HWE-based genotyper.
- Integrated and added new Dindel likelihood estimation model.
- Corrected annotators that would call readBasePileup: since we can be annotating extended events, best way is to interrogate context for kind of pileup and either readBasePileup or readExtendedEventPileup.
All changes above except last one are still in playground since they require more testing.
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the empty list. Score another victory for the integration tests.
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argument. Brought it back, and added an integrationtest to make sure it
stays around.
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the pileup at the next alignment start is large, we don't add as many of those
incoming reads as we should. No integration tests were affected.
Thanks, Chris!
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-- getToolkit().subContextFromSampleProperty(): filters a VariantContext to genotypes that come from samples that have a given property value
-- getToolkit().getSamplesWithProperty(): gets all samples with a given property
-- getToolkit().getSamplesFromVariantContext(): sample objects that are referenced by name in a VariantContext
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This will allow other programs like Queue to reuse the functionality.
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pieces of core that depend on playground. Most of these have been eliminated by
(temporarily) promoting Aaron's report system to core in this checkin. I'll
follow up with other changes in separately.
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The GAE half has all the walker specific code. The new "Abstract" GAE has the rest of the logic.
More refactoring to come, with the end goal of having a tool that other java analysis programs (Queue, etc.) can use to read in genomic data.
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Thanks to Ryan for identifying the problem.
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mOVsxGfDiiSMxVs2PPTVjzYTVbizlD6e
f9kUHUADFsZ0LiTGxRL5zPmq9kZcA4cQ
8eGHWJFAlBVmgxwPi3sMd1RmiN2PwHOf
iLhvHWveypKb2F8vKS5irHylc3pYvlOb
HDttXKUMEVoPrvVeWrH7E0htxYyNydMx
plus a bit of cleanup of custom exceptions in the sharding system.
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Added a pipeline java bean and YAML utility to serialize java beans.
Added a getFirehosePipelineYaml.sh that can pull firehose data into the pipeline yaml file format.
Updated the fullCallingPipeline.q to begin using the pipeline yaml file format for bams and reference.
More changes to come as this code gets tested out in the fullCallingPipeline.
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Changed integration tests, adding the -NO_HEADER argument, for walkers that previously did not include the command-line
arg headers.
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a) Redid way to compute path metrics in indel error model. Paper formulation where we have an anchor point in the alignemt between read and haplotype won't work in practice except in nice data sets that are perfectly indel-realigned and that are well mapped by aligner. New formulation doesn't assume this, and it's actually simpler and uses less code. It now resembles more a classic SW dynamic programming formulation but it still preserves the HMM probabilistic formulation.
b) Added a programmable call threshold, set by command line.
c) Use now sample name from BAM file, remove -sampleName argument.
d) Simplify loop to compute read-haplotype likelihoods.
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Ryan is using this to modify VCF code today...
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Also added a new error message that I thought would be helpful...
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fromer
asivache
depristo
hanna
ebanks
delangel
rpoplin
chartl
aaron
kiran
scalvo
bthomas
kshakir
corin