There are a few pipeline test classes that do not run Queue, but are
classified as pipeline tests because they submit farm jobs. Make these
unconventional pipeline tests respect the pipeline test dry run setting.
This is used in conjunction with the -BAM argument in AssessNA12878 and is necessary for the
Jenkins assessment to work properly (Ryan's commit wasn't enough).
I "fixed" this once before but instead of testing with unit tests I used integration tests.
Bad decision.
The proper fix is in now, with a bonafide unit test included.
1. MergeIntervalLists should take the global interval padding into account when merging.
2. Update the name of the imported callsets in the setup script because of renaming for expanded intervals.
3. If there are too many intervals to process, MongoDB falls apart. Refactored the site selection code so
that in such cases we pull out all records from the DB and the GATK itself does the interval filtering.
4. Add isComplex to callset summary for the consensus summarizer.
5. Remove the check for out of order records in the SiteIterator since records now do come out of order
(since contigs are sorted lexicographically in MongoDB).
Results:
Iteration over the gencode intervals (90 MB) in AssessNA12878 now takes 90 seconds. I can't tell you how
much time it took before because it kept crashing Mongo (but it was a long, long time).
Previous fixes and tests only covered trailing soft-clips. Now that up front
hard-clipping is working properly though, we were failing on those in the tool.
Added a patch for this as well as a separate test independent of the soft-clips
to make sure that it's working properly.
* Increase the memory limit for HTSLIB - Bam shuffling just eats up a ton of memory.
* Concurrent HTSLIB processes need unique temp files the bam shuffling step was messing up with the temporary files and failing without returning zero. Fixed it by giving a unique name to each process.
This time we don't accidentally drop reads (phew), but this bug does cause us not to
update the alignment start of the mate. Fixed and added unit test to cover it.
-- Added experimental LikelihoodRankSum, which required slightly more detailed access to the information managed by the base class, so added an overloaded getElementForRead also provides access to the MostLikelyAllele class
-- Added base class default implementation of getElementForPileupElement() which returns null, indicating that the pileup version isn't supported.
-- Added @Override to many of the RankSum classes for safety's sake
-- Updates to GeneralCallingPipeline: annotate sites with dbSNP IDs,
-- R script to assess the value of annotations for VQSR
-- The VR, when the model is bad, may evaluate log10sumlog10 where some of the values in the vector are NaN. This case is now trapped in VR and handled as previously -- indicating that the model has failed and evaluation continues.
-- Currently we don't support writing a BAM file from the haplotype caller when nct is enabled. Check in initialize if this is the case, and throw a UserException
Github was intermittently rejecting large pushes that were in fact
fast-forward updates as being non-fast-forward. Try to prevent this
by ensuring that all refs are up-to-date and properly checked out
after branch filtering and before doing a source release.
-- Previous version emitted command lines that look like:
##HaplotypeCaller="analysis_type=HaplotypeCaller input_file=[private/testdata/reduced.readNotFullySpanningDeletion.bam] ..."
the new version provides additional information on when the GATK was run and the GATK version in a nicer format:
##GATKCommandLine=<ID=HaplotypeCaller,Version=2.5-206-gbc7be2b,Date="Thu Jun 20 11:09:01 EDT 2013",Epoch=1371740941197,CommandLineOptions="analysis_type=HaplotypeCaller input_file=[private/testdata/reduced.readNotFullySpanningDeletion.bam] read_buffer_size=null phone_home=AWS ...">
-- Additionally, the command line options are emitted sequentially in the file, so you can see a running record of how a VCF was produced, such as this example from the integration test:
##GATKCommandLine=<ID=HaplotypeCaller,Version=2.5-206-gbc7be2b,Date="Thu Jun 20 11:09:01 EDT 2013",Epoch=1371740941197,CommandLineOptions="lots of stuff">
##GATKCommandLine=<ID=SelectVariants,Version=2.5-206-gbc7be2b,Date="Thu Jun 20 11:16:23 EDT 2013",Epoch=1371741383277,CommandLineOptions="lots of stuff">
-- Removed the ProtectedEngineFeaturesIntegrationTest
-- Actual unit tests for these features!
Improved AnalyzeCovariates (AC) integration test.
Renamed AC test files ending with .grp to .table
Implementation:
* Removed RECAL_PDF/CSV_FILE from RecalibrationArgumentCollection (RAC). Updated rest of the code accordingly.
* Fixed BQSRIntegrationTest to work with new changes
Implemtation details:
* Added tool class *.AnalyzeCovariates
* Added convenient addAll method to Utils to be able to add elements of an array.
* Added parameter comparison methods to RecalibrationArgumentCollection class in order to verify that multiple imput recalibration report are compatible and comparable.
* Modified the BQSR.R script to handle up to 3 different recalibration tables (-BQSR, -before and -after) and removed some irrelevant arguments (or argument values) from the output.
* Added an integration test class.
-Collapses zero-length and repeated cigar elements, neither of which
can necessarily be handled correctly by downstream code (like LIBS).
-Consolidation is done before read filters, because not all read filters
behave correctly with non-consoliated cigars.
-Examined other uses of consolidateCigar() throughout the GATK, and
found them to not be redundant with the new engine-level consolidation
(they're all on artificially-created cigars in the HaplotypeCaller
and SmithWaterman classes)
-Improved comments in SAMDataSource.applyDecoratingIterators()
-Updated MD5s; differences were examined and found to be innocuous
-Two tests: -Unit test for ReadFormattingIterator
-Integration test for correct handling of zero-length
cigar elements by the GATK engine as a whole
-This argument was completely redundant with the engine-level -dfrac
argument.
-Could produce unintended consequences if used in conjunction with
engine-level downsampling arguments.
Khalid Shakir
Francesco
Mark DePristo
Mauricio Carneiro
David Roazen
Ryan Poplin
Eric Banks
Jacob Silterra
Valentin Ruano-Rubio
Yossi Farjoun