-- Right now the state of the AFCaclulationResult can be corrupt (ie, log10 likelihoods can be -Infinity). Forced me to disable reasonable contracts. Needs to be thought through
-- exactCallsLog should be optional
-- Update UG integration tests as the calculation of the normalized posteriors is done in a marginally different way so the output is rounded slightly differently.
-- UnifiedGenotyperEngine no longer keeps a thread local double[2] array for the normalized posteriors array. This is way heavy-weight compared to just making the array each time.
-- Added getNormalizedPosteriorOfAFGTZero and getNormalizedPosteriorOfAFzero to AFResult object. That's the place it should really live
-- Add tests for priors, uncovering bugs in the contracts of the tri-allelic priors w.r.t. the AC of the MAP. Added TODOs
-- AFResult now tracks the number of evaluations (turns through the model calculation) so we can now compute the scaling of exact model itself as a function of n samples
-- Added unittests for priors (flat and human)
-- Discovered nasty general ploidy bug (enabled with Guillermo_FIXME)
-- Added combinatorial unit tests for both Diploid and General (in diploid-case) for 2 and 3 alleles in all combinations of sample types (i.e., AA, AB, BB and equiv. for tri-allelic). More assert statements to ensure quality of the result.
-- Added docs (DOCUMENT YOUR CODE!) to AlleleFrequencyCalculationResult, with proper input error handling and contracts. Made mutation functions all protected
-- No longer need to call reset on your AlleleFrequencyCalculationResult -- it'd done for you in the calculation function. reset is a protected method now, so it's all cleaner and nicer this way
-- TODO still -- need to add edge-case tests for non-informative samples (0,0,0), for the impact of priors, and I need to add some way to test the result of the pNonRef
-- Added a true base class that only does truly common tasks (like manage call logging)
-- This base class provides the only public method (getLog10PNonRef) and calls into a protected compute function that's abstract
-- Split ExactAF into superclass ExactAF with common data structures and two subclasses: DiploidExact and GeneralPloidyExact
-- Added an abstract reduceScope function that manages the simplification of the input VariantContext in the case where there are too many alleles or other constraints require us to only attempt a smaller computation
-- All unit tests pass
-- This allows us to log all of the information about the exact model call (alleles, priors, PLs, result, and runtime) to a file for later debugging / optimization
1) GATKArgumentCollection has a command to turn off randomization if setting the seed isn't enough. Right now it's only hooked into RankSumTest.
2) RankSumTest now can be passed a boolean telling it whether to use a dithering or non-randomizing comparator. Unit tested.
3) VariantsToBinaryPed can now output in both individual-major and SNP-major mode. Integration test.
4) Updates to PlinkBed-handling python scripts and utilities.
5) Tool for calculating (LD-corrected) GRMs put under version control. This is analysis for T2D, but I don't want to lose it should something happen to my computer.
Sometimes the GATK engine creates a single monolithic FilePointer representing all regions
in all BAM files. In such cases, the monolithic FilePointer is the only FilePointer emitted
by the BAMScheduler, and it's safe to allow it to contain regions and intervals from multiple
contigs.
This fixes support for reading unindexed BAM files (since an unindexed BAM is one case
in which the engine creates a monolithic FilePointer).
Nasty, nasty bug -- if we were extremely unlucky with shard boundaries, we might
end up with a shard containing only unmapped mates of mapped reads. In this case,
ReadShard.getReadsSpan() would not behave correctly, since the shard as a whole would
be marked "mapped" (since it refers to mapped intervals) yet consist only of unmapped
mates of mapped reads located within those intervals.
1) ValidateVariants removed in favor of direct validation VariantContexts. Integration test added to test broken contexts.
2) Enabling indel and SV output. Still bi-allelic sites only. Integration tests added for these cases.
3) Found a bug where GQ recalculation (if a genotype has PLs but no GQ) would only happen for flipped encoding. Fixed. Integration test added.
Merge all FilePointers for each contig into a single, merged, optimized FilePointer
representing all regions to visit in all BAM files for a given contig.
This helps us in several ways:
-It allows us to create a single, persistent set of iterators for each contig,
finally and definitively eliminating all Shard/FilePointer boundary issues for
the new experimental ReadWalker downsampling
-We no longer need to track low-level file positions in the sharding system (which
was no longer possible anyway given the new experimental downsampling system)
-We no longer revisit BAM file chunks that we've visited in the past -- all BAM
file access is purely sequential
-We no longer need to constantly recreate our full chain of read iterators
There are also potential dangers:
-We hold more BAM index data in memory at once. Given that we merge and optimize
the index data during the merge, and only hold one contig's worth of data at a
time, this does not appear to be a major issue. TODO: confirm this!
-With a huge number of samples and intervals, the FilePointer merge operation
might become expensive. With the latest implementation, this does not
appear to be an issue even with a huge number of intervals (for one sample, at least),
but if it turns out to be a problem for > 1 sample there are things we can do.
Still TODO: unit tests for the new FilePointer.union() method
-- Fixes monster bug in the way that traversal engines interacted with the NanoScheduler via the output tracker.
-- ThreadLocalOutputTracker is now a ThreadBasedOutputTracker that associates via a map from a master thread -> the storage map. Lookups occur by walking through threads in the same thread group, not just the thread itself (TBD -- should have a map from ThreadGroup instead)
-- Removed unnecessary debug statement in GenomeLocParser
-- nt and nct officially work together now
TestNG skips tests when an exception occurs in a data provider,
which is what was happening here.
This was due to an AWFUL AWFUL use of a non-final static for
ReadShard.MAX_READS. This is fine if you assume only one instance
of SAMDataSource, but with multiple tests creating multiple SAMDataSources,
and each one overwriting ReadShard.MAX_READS, you have a recipe for
problems. As a result of this the test ran fine individually, but not as
part of the unit test suite.
Quick fix for now to get the tests running -- this "mutable static"
interface should really be refactored away though, when I have time.
It's now possible to run with experimental downsampling enabled
using the --enable_experimental_downsampling engine argument.
This is scheduled to become the GATK-wide default next week after
diff engine output for failing tests has been examined.
Notify all downsamplers in our pool of the current global genomic position every
DOWNSAMPLER_POSITIONAL_UPDATE_INTERVAL position changes, not every single
positional change after that threshold is first reached.
-Only used when experimental downsampling is enabled
-Persists read iterators across shards, creating a new set only when we've exhausted
the current BAM file region(s). This prevents the engine from revisiting regions discarded
by the downsamplers / filters, as could happen in the old implementation.
-SAMDataSource no longer tracks low-level file positions in experimental mode. Can strip
out all related code when the engine fork is collapsed.
-Defensive implementation that assumes BAM file regions coming out of the BAM Schedule
can overlap; should be able to improve performance if we can prove they cannot possibly
overlap.
-Tests a bit on the extreme side (~8 minute runtime) for now; will scale these back
once confidence in the code is gained
-- See https://jira.broadinstitute.org/browse/GSA-573
-- Uses InheritedThreadLocal storage so that children threads created by the NanoScheduler see the parent stubs in the main thread.
-- Added explicit integration test that checks that -nt 1, 2 and -nct 1, 2 give the same results for GLM BOTH with the UG over 1 MB.
Doesn't actually fix the problem, and adds an unnecessary delay in closing down NanoScheduler, so reverting.
This reverts commit 66b820bf94ae755a8a0c71ea16f4cae56fd3e852.
1) Better documentation on the meta data file for VariantsToBinaryPed with examples of each file type
2) MannWhitneyU can now take an argument on creation to turn off dithering. This pertains to JIRA-GSA-571 but does not fix it,
as it isn't hooked up to the command line. Next step is to add an argument to the command line where it's accessible to the
annotation classes (e.g. from either UG or the VariantAnnotator).
3) Added some dumb python scripts to deal with Plink files, and a script to convert plink binaries to VCF to help sanity check. Basically if you want to do an analysis on genotype data stored in plink binary format, your choices are:
1) Add a new module to Plink [difficulty rating: Impossible -- code obfuscation]
2) Steal plink parsing code from software (Plink/PlinkSeq/GCTA/Emacks/etc) that readds the files [difficulty rating: Oppressive -- code not modularized at all)
3) Write your own dumb stuff [difficutly rating: Annoying]
What's been added is the result of 3. It's a library so nobody else has to do this, so long as they're comfortable with python.
-- Renamed TraversalErrorManager to the more general MultiThreadedErrorTracker
-- ErrorTracker is now used throughout the NanoScheduler. In order to properly handle errors, the work previously done by main thread (submit jobs, block on reduce) is now handled in a separate thread. The main thread simply wakes up peroidically and checks whether the reduce result is available or if an error has occurred, and handles each appropriately.
-- EngineFeaturesIntegrationTest checks that -nt and -nct properly throw errors in Walkers
-- Added NanoSchedulerUnitTest for input errors
-- ThreadEfficiencyMonitoring is now disabled by default, and can be enabled with a GATK command line option. This is because the monitoring doesn't differentiate between threads that are supposed to do work, and those that are supposed to wait, and therefore gives misleading results.
-- Build.xml no longer copies the unittest results verbosely
-- Refactored error handling from HMS into utils.TraversalErrorManager, which is now used by HMS and will be usable by NanoScheduler
-- Generalized EngineFeaturesIntegrationTest to test map / reduce error throwing for nt 1, nt 2 and nct 2 (disabled)
-- Added unit tests for failing input iterator in NanoScheduler (fails)
-- Made ErrorThrowing NanoScheduable
-- V3 + V4 algorithm for NanoScheduler. The newer version uses 1 dedicated input thread and n - 1 map/reduce threads. These MapReduceJobs perform map and a greedy reduce. The main thread's only job is to shuttle inputs from the input producer thread, enqueueing MapReduce jobs for each one. We manage the number of map jobs now via a Semaphore instead of a BlockingQueue of fixed size.
-- This new algorithm should consume N00% CPU power for -nct N value.
-- Also a cleaner implementation in general
-- Vastly expanded unit tests
-- Deleted FutureValue and ReduceThread
-- For the pooled caller we were writing diploid no-calls even when other samples were haploid. Changed maxPloidy function to return a defaultPloidy, rather than 0, in the case where all samples are missing.
-- VCF/BCF Writers now create missing genotypes with the ploidy of other samples, or 2 if none are available at all.
-- Updating integration tests for general ploidy, as previously we wrote ./. even when other calls were 0/0/0/0/0/0/0/0/0/0/0/0/0/0/0/0/0/0/0/1/1/1/1/1, but now we write ./././././././././././././././././././././././. (ugly but correct)
-- Previous code was looking for a -1 result from maxPloidy() but the result as actually 0, so instead of writing a diploid no call we were actually writing "unavailable" genotypes, and failing the BCF == VCF test in integration tests. Fixed.
-- Turns out this was consuming 30% of the UG runtime, and causing problems elsewhere.
-- Removed addMissingSamples from VariantcontextUtils, and calls to it
-- Updated VCF / BCF writers to automatically write out a diploid no call for missing samples
-- Added unit tests for this behavior in VariantContextWritersUnitTest
1) SelectVariants could throw a ReviewedStingException (one of the nasty "Bug:") ones if the user requested a sample that wasn't present in the VCF. The walker now
checks for this in the initialize() phase, and throws a more informative error if the situation is detected. If the user simply wants to subset the VCF to
all the samples requested that are actually present in the VCF, the --ALLOW_NONOVERLAPPING_COMMAND_LINE_SAMPLES flag changes this UserException to a Warning,
and does the appropriate subsetting. Added integration tests for this.
2) GenotypeLikelihoods has an unsafe method getLog10GQ(GenotypeType), which is completely broken for multi-allelic sites. I marked that method
as deprecated, and added methods that use the context of the allele ordering (either directly specified or as a VC) to retrieve the appropriate GQ, and
added a unit test to cover this case. VariantsToBinaryPed needs to dynamically calculate the GQ field sometimes (because I have some VCFs with PLs but no GQ).
-- Now prints out a single combined NanoScheduler runtime profile report across all nano schedulers in use. So now if you run with -nt 4 you'll get one combined NanoScheduler profiler across all 4 instances of the NanoScheduler within TraverseXNano.
-- Basically you cannot safely use instance specific ThreadLocal variables, as these cannot be safely cleaned up. The old implementation kept pointers to old writers, with huge tribble block indexes, and eventually we crashed out of integration tests
-- See http://weblogs.java.net/blog/jjviana/archive/2010/06/10/threadlocal-thread-pool-bad-idea-or-dealing-apparent-glassfish-memor for more information
-- New implementation uses a borrow/return schedule with a list of N TraversalEngines managed by the MicroScheduler directly.
-- Can now say -nt 4 and -nct 4 to get 16 threads running for you!
-- TraversalEngines are now ThreadLocal variables in the MicroScheduler.
-- Misc. code cleanup, final variables, some contracts.
-- TraversalProgressMeter now completely generalized, named ProgressMeter in utils.progressmeter. Now just takes "nRecordsProcessed" as an argument to print reads. Completely removes dependence on complex data structures from TraversalProgressMeter. Can be used to measure progress on any task with processing units in genomic locations.
-- a fairly simple, class with no dependency on GATK engine or other features.
-- Currently only used by the TraversalEngine / MicroScheduler but could be used for any purpose now, really.
-- Previously these core progress metering functions were all in TraversalEngine, and available to subclasses like TraverseLoci via inheritance. The problem here is that the upcoming data threads x cpu threads parallelism requires one master copy of the progress metering shared among all traversals, but multiple instantiations of traverse engines themselves.
-- Because the progress metering code has horrible anyway, I've refactored and vastly cleaned up and simplified all of these capabilities into TraversalProgressMeter class. I've simplified down the classes it uses to work (STILL SOME TODOs in there) so that it doesn't reach into the core GATK engine all the time. It should be possible to write some nice tests for it now. By making it its own class, it can protect itself from multi-threaded access with a single synchronized printProgress function instead of carrying around multiple lock objects as before
-- Cleaned up the start up of the progress meter. It's now handled when the meter is created, so each micro scheduler doesn't have to deal with proper initialization timing any longer
-- Simplified and made clear the interface for shutting down the traversal engines. There's no a shutdown method in TraversalEngine that's called once by the MicroScheduler when the entire traversing in over. Nano traversals now properly shut down (was subtle bug I undercovered here). The printing of on traversal done metering is now handled by MicroScheduler
-- The MicroScheduler holds the single master copy of the progress meter, and doles it out to the TraversalEngines (currently 1 but in future commit there will be N).
-- Added a nice function to GenomeAnalysisEngine that returns the regions we will be processing, either the intervals requested or the whole genome. Useful for progress meter but also probably for other infrastructure as well
-- Remove a lot of the sh*ting Bean interface getting and setting in MicroScheduler that's no longer useful. The generic bean is just a shell interface with nothing in it.
-- By removing a lot of these bean accessors and setters many things are now final that used to be dynamic.
This will prevent bugs from occurring when Vanilla make changes to the API
as described here: http://vanillaforums.com/blog/api#configuration
Based on the bug that broke the website Guide section on 9/6/12,
the GATKDocs posting system will probably break in the next release if
this is not applied as a bug fix.
-- I've rewritten the entire NS framework to use a producer / consumer model for input -> map and from map -> reduce. This is allowing us to scale reasonably efficiently up to 4 threads (see figure). Future work on the nano scheduler will be itemized in a separate JIRA entry.
-- Restructured the NS code for clarity. Docs everywhere.
-- This is considered version 1.0
-Off by default; engine fork isolates new code paths from old code paths,
so no integration tests change yet
-Experimental implementation is currently BROKEN due to a serious issue
involving file spans. No one can/should use the experimental features
until I've patched this issue.
-There are temporarily two independent versions of LocusIteratorByState.
Anyone changing one version should port the change to the other (if possible),
and anyone adding unit tests for one version should add the same unit tests
for the other (again, if possible). This situation will hopefully be extremely
temporary, and last only until the experimental implementation is proven.
-- The NanoScheduler is doing a good job at tracking important information like time spent in map/reduce/input etc.
-- Can be disabled with static boolean in MicroScheduler if we have problems
-- See GSA-515 Nanoscheduler GSA-549 Retire TraverseReads and TraverseLoci after testing confirms nano scheduler version in single threaded version is fine
-- Closes GSA-515 Nanoscheduler GSA-542 Good interface to nanoScheduler
-- Old -nt means dataThreads
-- New -cnt (--num_cpu_threads_per_data_thread) gives you n cpu threads for each data thread in the system
-- Cleanup logic for handling data and cpu threading in HMS, LMS, and MS
-- GATKRunReport reports the total number of threads in use by the GATK, not just the nt value
-- Removed the io,cpu tags for nt. Stupid system if you ask me. Cleaned up the GenomeAnalysisEngine and ThreadAllocation handling to be totally straightforward now
-- Separate updating cumulative traversal metrics from printing progress. There's now an updateCumulativeMetrics function and a printProgress() that only takes a current position
-- printProgress now soles relies on the time since the last progress to decide if it will print or not. No longer uses the number of cycles, since this isn't reliable in the case of nano scheduling
-- GenomeAnalysisEngine now maintains a pointer to the master cumulative metrics. getCumulativeMetrics never returns null, which was handled in some parts of the code but not others.
-- Update all of the traversals to use the new updateCumulativeMetrics, printProgress model
-- Added progress callback to nano scheduler. Every bufferSize elements this callback is invoked, allowing us to smoothly update the progress meter in the NanoScheduler
-- Rename MapFunction to NanoSchedulerMap and the same for reduce.
-- Refactored TraverseLoci into old linear version and nano scheduling version
-- Temp. GATK argument to say how many nano threads to use
-- Can efficiently scale to 3 threads before blocking on input
-- Instead of returning directly the result of map(), returns a MapResult object with the value and a reduceMe flag.
-- Reduce function respects the reduceMe flag
-- Code cleanup and more documentation
-- Helpful for understanding where the time goes to each bit of the code.
-- Controlled by a local static boolean, to avoid the potential overhead in general
-- TraverseReadsNano prints progress at the end of each traversal unit
-- Fix bugs in TraversalEngine printProgress
-- Synchronize the method so we don't get multiple logged outputs when two or more HMSs call printProgress before initialization at the start!
-- Fix the logic for mustPrint, which actually had the logic of mustNotPrint. Now we see the done log line that was always supposed to be there
-- Fix output formatting, as the done() line was incorrectly shifting over the % complete by 1 char as 100.0% didn't fit in %4.1f
-- Add clearer doc on -PF argument so that people know that the performance log can be generated to standard out if one wants
- VariantAnnotatorEngine changed to call genotype annotations even if pilups and allele -> likelihood mappings are not present. Current genotype annotations altered to check for null pilupes and null mappings.
-- Confirmed that reads spanning off the end of the chromosome don't cause an exception by adding integration test for a single read that starts 7 bases from the end of chromosome 1 and spans 90 bases or so off. Added pileup integration test to ensure this behavior continues to work
-- In the process uncovered two strange things
1 -- qualityScoreByFullCovariateKey was created but never used. Seems like a cache?
2 -- Discovered nasty bug in BaseRecalibrator: https://jira.broadinstitute.org/browse/GSA-534
-- These are like read filters but can be applied either on input, on output, of handled by the walker
-- Previous example of BAQ now uses the general framework
-- Resulted in massive conceptual cleanup of SAMDataSource and ReadProperties! Yeah!
-- BQSR now uses this framework. We can now do BQSR on input, on output, or within a walker
-- PrintReads now handles all read transformers in the walker in map, enabling us to parallelize PrintReads with BAQ and BQSR
-- Currently BQSR is excepting in parallel, which subsequent commit with fix
-- Removed global variable setting in GenomeAnalysisEngine for BAQ, as command line parameters are cleanly handled by ReadTransformer infrastructure
-- In principle ReadFilters are just a special kind of ReadTransformer, but this refactoring is larger than I can do. It's a JIRA entry
-- Many files touched simply due to the refactoring and renaming of classes
-- A higher level interface to declare parallelism capability of a walker. This interface means that the walker can be multi-threaded, but doesn't necessarily support TreeReducible interface, which forces you to have a combine ReduceType operation that isn't appropriate for parallel read walkers
-- Updated ReadWalkers to implement ThreadSafeMapReduce not TreeReducible
-- TraverseReadsNano modified to read in all input data before invoking maps, so the input to TraverseReadsNano is a MapData object holding the sam record, the ref context, and the refmetadatatracker.
-- Update ValidateRODForReads to be tree reducible, using synchronized map and explicitly sort the output map from locations -> counts in onTraversalDone
-- Expanded integration tests to test nt 1, 2, 4.
-- Yes, GenomeLoc.compareTo was broken. The compareTo function only considered the contig and start position, but not the stop, when comparing genome locs.
-- Updated GenomeLoc.compareTo function to account for stop. Updated GATK code where necessary to fix resulting problems that depended on this.
-- Added unit tests to ensure that hashcode, equals, and compareTo are all correct for GenomeLocs
In addition, fix for GSA-310. If supplied -rf argument does not match a known read filter, the list of read filters will be printed, and users directed to the documentation for more information.
-- Stateless objects are required for nano-scheduling. This means you can take the RefMetaDataTracker provided by ReadBasedReferenceOrderedView, store it way, get another from the same view, and the original one behaves the same.
-- Previous behavior was unnecessary and causes all sorts of problems with RODs for reads. The old implementation simply failed in this case. The new code handles this correctly by forcing shards to have all of their data on a single contig.
-- Added a PrintReads integration test to ensure this behavior is correct
-- Adding test BAMs that have < 200 reads and span across contig boundaries
-- shardSpan is only calculated when there some ROD is live in the GATK. No sense in paying the cost per read when you don't need it
-- Update contract to allow null span or unmapped span (good catch unittests!)
-- Deleted ReadMetaDataTracker
-- Added function to ReadShard to give us the span from the left most position of the reads in the shard to the right most, which is needed for the new view
-- ReadMetaDataTracker is dead! Long live the RefMetaDataTracker. Read walkers will soon just take RefMetaDataTracker objects. In this commit they take a class that trivially extends them
-- Rewrote ReadBasedReferenceOrderedView to produce RefMetaDataTrackers not the old class.
-- This new implementation produces thread-safe objects (i.e., holds no points to shared state). Suitable for use (to be tested) with nano scheduling
-- Simplified interfaces to use the simplest data structures (PeekableIterator) not the LocusAwareSeekableIterator, since I both hate those classes and this is on the long term trajectory to remove those from the GATK entirely.
-- Massively expanded DataProvider unit tests for ReadBasedReferenceOrderedView
-- Note that the old implementation of offset -> ROD in ReadRefMetaDataTracker was broken for any read not completely matching the reference. Rather than provide broken code the ReadMetaDataTracker only provides a "bag of RODs" interface. If you want to work with the relationship between the read and the RODs in your tool you need to manage the CIGAR element itself.
-- This commit breaks the new read walker BQSR, but Ryan knows this is coming
-- Subsequent commit will be retiring / fixing ValidateRODForReads
Reverting back to the original implementation, but now including write N's and write Q0's due to walkers that look at the same read multiple times in different reference windows
-- Old way (filtering for Q > 17 bases) resulted in biased FS when the site was good but there was a
systematic shift in the QUAL of REF and ALT between strands of the reads (sometimes happens)
-- New way (taking all bases) was consistent with BaseQualRankSum and other tests, but there can be
a lot of low qual reference bases on one strand in some techs (ION/PROTON/PACBIO) because of the
preference for introducing an indel vs. a mismatch.
-- This implementation allows us to have our cake and eat it to by computing both p-values, and
taking the maximum one (i.e., least significant).
-- No integration tests updated yet -- still exploring the consequences of this change
-- TraversalReadsNano only creates the NanoScheduler once, and shuts it down onTraversalDone
-- Nicer debugging output in NanoScheduler
-- ReadShard has a getBufferSize() method now
-- I'm seeing a lot of people trying to use BinaryTagCovariate in the community. They really shouldn't do this, so I moved it to private.
-- Throw an exception if its required bintag argument is missing
-- Check explicitly if user is requesting DinucCovariate and tell them that its been retired in favor of ContextCovariate
-- Show the type (Required, Experimental, Standard) of the covariates when running --list
A number of functions int he sampleDB looked to be assuming that samples could not share IDs (e.g. sample IDs are unique, so a sample present in two families could not be represented by multiple Sample objects). Added an assertion in the SampleDBBuilder to document/test this assumption.
MVLikelihoodRatio now uses the trio methods from SampleDB.
-- Groups inputs for each thread so that we don't have one thread execution per map() call
-- Added shutdown function
-- Documentation everywhere
-- Code cleanup
-- Extensive unittests
-- At this point I'm ready to integrate it into the engine for CPU parallel read walkers
– Write general NanoScheduler framework in utils.threading. Test with reading via iterator from list of integers, map is int * 2, reduce is sum. Should be efficiency using resources to do sum of 2 * (sum(1 - X)).
Done!
CPU parallelism is nano threads. Pfor across read / map / reduce. Use work queue to implement.
Create general read map reduce framework in utils. Test parallelism independently before hooking up to Locus iterator
Represent explicitly the dependency graph. Scheduler should choose the work units that are ready for computation, that are marked as "completing a computation", and then finally that maximize the number of sequent available work units. May be worth measuring expected cost for read read / map / reduce unit and use it to balance the compute
As input is single threaded just need one thread to populate inputs, which runs as fast as possible on parallel pushing data to fixed size queue. Each push creates map job and links to upcoming reduce job.
Note that there's at most one thread for IO tasks, and all of the threads can contribute to CPU tasks
-- GATKRunReports contain itemized information about the numThreads used to execute the GATK, as well as the efficiency of the use of those threads to get real work done, including time spent running, waiting, blocking, and waiting for IO
-- See https://jira.broadinstitute.org/browse/GSA-506 for more details
-- Invert logic in GATKArgumentCollection to disable monitoring, not enable. That means monitoring is on by default
-- Fix testing error in unit tests
-- Rename variables in ThreadAllocation to be clearer
-- Old version StateMonitoringThreadFactory refactored into base class ThreadEfficiencyMonitor and subclass EfficiencyMonitoringThreadFactory.
-- Base class is used by LinearMicroScheduler to monitor performance of GATK in single threaded mode
-- MicroScheduler now handles management of the efficiency monitor. Includes master thread in monitor, meaning that reduce is now included for both schedulers
-- Allows us to ID (by proxy) time spent doing IO
-- Refactor StateMonitoryingThreadFactory to use it's own enum, not Thread.State
-- Reliable unit tests across mac and unix
-- See https://jira.broadinstitute.org/browse/GSA-502
-- New command line argument -mt enables thread monitoring
-- If enabled, HMS uses StateMonitoringThreadFactory to create monitored threads, and prints out an efficiency report when HMS exits, telling the user information like:
for BQSR – known to be inefficient locking
INFO 17:10:33,195 StateMonitoringThreadFactory - Number of activeThreads used: 8
INFO 17:10:33,196 StateMonitoringThreadFactory - Total runtime 90.3 m
INFO 17:10:33,196 StateMonitoringThreadFactory - Fraction of time spent blocked is 0.72 ( 64.8 m)
INFO 17:10:33,197 StateMonitoringThreadFactory - Fraction of time spent running is 0.26 ( 23.7 m)
INFO 17:10:33,197 StateMonitoringThreadFactory - Fraction of time spent waiting is 0.02 ( 112.8 s)
INFO 17:10:33,197 StateMonitoringThreadFactory - Efficiency of multi-threading: 26.19% of time spent doing productive work
for CountLoci
INFO 17:06:12,777 StateMonitoringThreadFactory - Number of activeThreads used: 8
INFO 17:06:12,777 StateMonitoringThreadFactory - Total runtime 43.5 m
INFO 17:06:12,778 StateMonitoringThreadFactory - Fraction of time spent blocked is 0.00 ( 4.2 s)
INFO 17:06:12,778 StateMonitoringThreadFactory - Fraction of time spent running is 1.00 ( 43.3 m)
INFO 17:06:12,779 StateMonitoringThreadFactory - Fraction of time spent waiting is 0.00 ( 6.0 s)
INFO 17:06:12,779 StateMonitoringThreadFactory - Efficiency of multi-threading: 99.61% of time spent doing productive work
- Fix for M_Trieb's error report on the forum, and addition of integration tests to cover the walker.
- Addition of StructuralIndel as a class of variation within the VariantContext. These are for variants with a full alt allele that's >150bp in length.
- Adaptation of the MVLikelihoodRatio to work for a set of trios (takes the max over the trios of the MVLR)
- InsertSizeDistribution changed to use the new gatk report output (it was previously broken)
- RetrogeneDiscovery changed to be compatible with the new gatk report
- A maxIndelSize argument added to SelectVariants
- ByTranscriptEvaluator rewritten for cleanliness
- VariantRecalibrator modified to not exclude structural indels from recalibration if the mode is INDEL
- Documentation added to DepthOfCoverageIntegrationTest (no, don't yell at chartl ;_; )
Also sorry for the long commit history behind this that is the result of fixing merge conflicts. Because this *also* fixes a conflict (from git stash apply), for some reason I can't rebase all of them away. I'm pretty sure some of the commit notes say "this note isn't important because I'm going to rebase it anyway".
-- When merging multiple VCF records at a site, the combined VCF record has the QUAL of the first VCF record with a non-MISSING QUAL value. The previous behavior was to take the max QUAL, which resulted in sometime strange downstream confusion.
* No reads with Hard/Soft clips in the middle of the cigar
* No reads starting with deletions (with or without preceding clips)
* No reads ending in deletions (with or without follow-up clips)
* No reads that are fully hard or soft clipped
* No reads that have consecutive indels in the cigar (II, DD, ID or DI)
Also added systematic test for good cigars and iterative test for bad cigars.
-- Removed REFERENCE_BASES option. You only have REFERENCE now. There's no efficiency savings for the REFERENCE_BASES option any longer, since the reference bases are loaded lazy so if you don't use them there's effectively no cost to making the RefContext that could load them.
-- The GATK sort of handles this now, but only if you have the exactly correct sequence dictionary and FAI files associated with the reference. If you do, the file can be .gz. If not, the GATK will fail on creating the FAI and DICT files. Added an error message that handles this case and clearly says what to do.
-- Now blows up if an argument begins with -. Implementation isn't pretty, as it actually blows up during Queue extension creation with a somewhat obscure error message but at least its something.
-- Keep reading from BCF2 input stream when read(byte[]) returns < number of needed bytes
-- It's possible (I think) that the failure in GSA-484 is due to multi-threading writing/reading of BCF2 records where the underlying stream is not yet flushed so read(byte[]) returns a partial result. No loops until we get all of the needed bytes or EOF is encounted
Major idea is that per-read haplotype likelihoods are now stored in a single unified object of class PerReadAlleleLikelihoodMap. Class implementation in theory hides internal storage details from outside work (still may need work cleaning up interface), and this object(or rather, a Map from Sample->perReadAlleleLikelihoodMap) is produced by UGCalcLikelihoods. The genotype calculation is also able to potentially use this info if needed. All InfoFieldAnnotations now get an extra argument with this map. Currently, this map is only produced for indels in UG, or for all variants within HaplotypeCaller. If this map is absent (SNPs in UG), the old Pileup interface is used, but it's avoided whenever possible. FORMAT annotations are not yet changed but will be focus of second step. Major benefit will be that annotations will be able to very easily discard non-informative reads for certain events. HaplotypeCaller also uses this new class, and no longer hard-codes the mapping of allele ->list(reads) but instead uses the same objects and interfaces as the rest of the modules. Code still needs further testing/cleaning/reviewing/debugging
-- Removed half-a*ssed attempt to automatically repair VCF files with bad headers, which allowed users to provide a replacement header overwriting the file's actually header on the fly. Not a good idea, really. Eric has promised to create a utility that walks through a VCF file and creates a meaningful header field based on the file's contents (if this ever becomes a priority)
-- Now possible to do -o /dev/stdout -bcf -l DEBUG > tmp.bcf and create a valid BCF2 file
-- Cleanup code to make sure extensions easier by moving to a setX model in VariantContextWriterStub
-- BCF2 is failing for some reason when merging tmp. files with parallel combine variants. ThreadLocalOutputTracker no longer sets deleteOnExit on the tmp file, as this prevents debugging. And it's unnecessary because each mergeInto was deleting files as appropriate
-- MergeInfo in VariantContextWriterStorage only deletes the intermediate output if an error occurs
-- All tests but one (using old bad VCF3 input) run unmodified with parallel code.
-- Disabled UNSAFE_VCF_PROCESSING for all but that test, which changes md5s because the output files have fixed headers
-- Minor optimizations to simpleMerge
-- BCF2 now determines whether it can safely write out raw genotype blocks, which is true in the case where the VCF header of the input is a complete, ordered subset of the output header. Added utilities to determine this and extensive unit tests (headerLinesAreOrderedConsistently)
-- Cleanup collapseStringList and exploreStringList for new unit tests of BCF2Utils. Fixed bug in edge case that never occurred in practice
-- VCFContigHeaderLine now provides its own key (VCFHeader.CONTIG_KEY) directly instead of requiring the user to provide it (and hoping its right)
-- More ways to access the data in VCFHeader
-- BCF2Writer uses a cache to avoid recomputing unnecessarily whether raw genotype blocks can be emitted directly into the output
-- Optimization of fullyDecodeAttributes -- attributes.size() is expensive and unnecessary. We just guess that on average we need ~10 elements for the attribute map
-- CombineVariants optimization -- filters are online HashSet but are sorted at the end by creating a TreeSet
-- makeCombinations is now makePermutations, and you can request to create the permutations with or without replacement
-- CombineVariants is now TreeReducible!
-- Integration tests running in parallel all pass except one (will fix) due to incorrect use of db=0 flag on input from old VCF format
-- Previous IO stub was hardcoded to write VCF. So when you ran -nt 2 -o my.bcf you actually created intermediate VCF files that were then encoded single threaded as BCF. Now we emit natively per thread BCF, and use the fast mergeInfo code to read BCF -> write BCF. Upcoming optimizations to avoid decoding genotype data unnecessarily will enable us to really quickly process BCF2 in parallel
-- VariantContextWriterStub forces BCF output for intermediate files
-- Nicer debug log message in BCF2Codec
-- Turn off debug logging of BCF2LazyGenotypesDecoder
-- BCF2FieldWriterManager now uses .debug not .info, so you won't see all of that field manager debugging info with BCF2 any longer
-- VariantContextWriterFactory.isBCFOutput now has version that accepts just a file path, not path + options
-- Expanded unit tests
-- Support for clean logging of results to logger
-- Refactored MyTime into AutoFormattingTime in Utils, out of TraversalEngine, for cleanliness and reuse
-- Added docs and contracts to StateMonitoringThreadFactory
-- GenomeLocParser cache was a major performance bottleneck in parallel GATK performance. With 10 thread > 50% of each thread's time was spent blocking on the MasterSequencingDictionary object. Made this a thread local variable.
-- Now we can run the GATK with 48 threads efficiently on GSA4!
-- Running -nt 1 => 75 minutes (didn't let is run all of the way through so likely would take longer)
-- Running -nt 24 => 3.81 minutes
-- The previously expanded ones are actually the missing values in the range. The previous ranges were correct. Removed the TODO to confirm them, as they are now officially confirmed
-- Includes header page
-- Table of arguments (Arguments)
-- Summary of counts (RecalData0)
-- Summary of counts by qual (RecalData1)
-- Fixed bug in output that resulted in covariates list always being null (updated md5s accordingly)
-- BQSR.R loads all relevant libaries now, include gplots, grid, and gsalib to run correctly
-- Added Write method to BCF2 types that directly converts int value to byte stream. Deleted writeRawBytes(int)
-- encodeTypeDescriptor semi-inlined into encodeType so that the tests for overflow are done in just one place
-- Faster implementation of determineIntegerType for int[] values
-- BCF2Type enum has an overloaded method to read the type as an int from an input stream. This gets rid of a case statement and replaces it with just minimum tiny methods that should be better optimized. As side effect of this optimization is an overall cleaner code organization
-- All low-level reads throw IOException instead of catching it directly. This allows us to not try/catch in readByte, improving performance by 5% or so
-- Optimize encodeTypeDescriptor with final variables. Avoid using Math.min instead do inline comparison
-- Inlined willOverflow directly in its single use
-- Old version converted doubles directly from strings. New version uses VariantContext getAttributeAsDouble() that looks at the values directly to determine how to convert from Object to Double (via Double.valueOf, (Double), or (Double)(Integer)).
-- getAttributeAsDouble() is now smart in converting integers to doubles as needed
-- Removed unnecessary logging info in BCF2Codec
-- Added integration tests to ensure that VQSR works end-to-end with BCF2 using sites version of the file khalid sent to me
-- Added vqsr.bcf_test.snps.unfiltered.bcf file for this integration test
-- Added bonferroni corrected p-value pruning, so you tell it how significant of a different you are willing to collapse in the tree, and it prunes the tree down to this maximum threshold
-- Penalty is now a phred-scaled p-value not the raw chi2 value
-- Split command line arguments in VisualizeContextTree into separate arguments for each type of pruning
-- Basically I was treating the context history in the wrong direction, effectively predicting the further bases in the context based on the closer one. Totally backward. Updated the code to build the tree in the right direction.
-- Added a few more useful outputs for analysis (minPenalty and maxPenalty)
-- Misc. cleanup of the code
-- Overall I'm not 100% certain this is even the right way to think about the problem. Clearly this is producing a reasonable output but the sum of chi2 values over the entire tree is just enormous. Perhaps a MCMC convergence / sampling criterion would be a better way to think about this problem?
-- Better output file name defaults
-- Fixed nasty bug where I included non-existant quals in the contexts to process because they showed up in the Cycle covariate
-- Data is processed in qual order now, so it's easier to see progress
-- Logger messages explaining where we are in the process
-- When in UPDATE mode we still write out the information for an equivalent prune by depth for post analysis
-- VisualizeContextTree now can write out an equivalent BQSR table determined after adaptive context merging of all RG x QUAL x CONTEXT trees
-- Docs, algorithm descriptions, etc so that it makes sense what's going on
-- VisualizeContextTree should really be simplified when into a single tool that just visualize the trees when / if we decide to make adaptive contexts standard part of BQSR
-- Misc. cleaning, organization of the code (recalibation tests were in private but corresponding actual files were public)
-- We are no likely to fail with an error when reading old BCF files, rather than just giving bad results
-- Added new class BCFVersion that consolidates all of the version management of BCF
-- Previous version would count all alt alleles as present in a sample, even if only 1 were present, because of the way VariantEval subsetted VCs
-- Updated code for subsetting VCs by sample to be clearer about how it handles rederiving alleles
-- Update a few pieces of code to get previous correct behavior
-- Updated a few MD5s as now ref calls at sites in dbSNP are counted as having a comp sites, and therefore show up in known sites when Novelty strat is on (which I think is correct)
-- Walkers that used old subsetting function with true are now using clearer version that does rederive alleles by default
-- Uses chi2 test for independences to determine if subcontext is worth representing. Give excellent visual results
-- Writes out analysis output file producing excellent results in R
-- Trivial reformatting of MathUtils
-- Reorganize functions in RecalDatum so that error rate can be computed indepentently. Added unit tests. Removed equals() method, which is a buggy without it's associated implementation for hashcode
-- New class RecalDatumTree based on QualIntervals that inherits from RecalDatum but includes the concept of sub data
-- VisualizeContextTree now uses RecalDatumTree and can trivially compute the penalty function for merging nodes, which it displays in the graph
-- Moved most of BQSR classes (which are used throughout the codebase) to utils.recalibration. It's better in my opinion to keep commonly used code in utils, and only specialized code in walkers. As code becomes embedded throughout GATK its should be refactored to live in utils
-- Removed unncessary imports of BQSR in VQSR v3
-- Now ready to refactor QualQuantizer and unit test into a subclass of RecalDatum, refactor unit tests into RecalDatum unit tests, and generalize into hierarchical recal datum that can be used in QualQuantizer and the analysis of adaptive context covariate
-- Update PluginManager to sort the plugins and interfaces. This allows us to have a deterministic order in which the plugin classes come back, which caused BQSR integration tests to temporarily change because I moved my classes around a bit.
-- Moved Datum, the now unnecessary superclass, into RecalDatum
-- Fixed some obviously dangerous synchronization errors in RecalDatum, though these may not have caused problems because they may not have been called in parallel mode
-- Check if a traversal error occurred in the last shard
-- Catch ExecutionException from the TreeReducer and throw as our HMS execption
-- ShardTraverser just throws the exception as formatted by the HMS, rather than wrapping it as a RuntimeException itself
-- EngineFeaturesIntegrationTests now uses public exampleFASTA (faster), and does 1000x iterations (slower)
-- Better error message when a traveral error occurs (a real bug)
-- EngineFeaturesIntegrationTest runs the multi-threaded error testing routines 50x times
-- A bit of cleanup in WalkerTest
We will use DocumentedGATKFeatures to create categories in our documentation. Eric I guess will be in charge of this. We need to remove walkers and think how to categorize everything.
Tools can be hidden from GATKdocs with the @Hidden annotation
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
-- VariantFiltration now properly sets passFilters in VC
-- BCF2 writer now properly decodes lazy BCF genotype data that it uses. Improper use generated a horrible subtle bug but the good news is that the extra checks I put in (unnecessarily a few days ago) caught the bug!
Signed-off-by: Mark DePristo <depristo@broadinstitute.org>
-- Always decode genotypes block when writing out a BCF file. If the header changes (and we currently don't know this easily) then the dictionary keys used in the genotypes block may be invalid. Temporarily added a private static boolean that turns off writing of the blocks until Eric and his team rewrite the header.
Signed-off-by: Mark DePristo <depristo@broadinstitute.org>
GATKDocs looks for a key on gsa4, and updates the forum with new walker if it exists.
More changes were made to the GATKDocs. Works nicely with bootstrap on and offline.
Cleaned up the code as well
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
Parameter wasn't working outside of the BQSR walker. It now takes the information on the recalibration report in other tools (PrintReads for example) and treats all reads as coming from the defined default platform.
* Did not touch archived walkers... those can be named whatever.
* Kept abstract classes that end in Walker untouched (e.g. LocusWalker, ReadWalker, ...)
* Renamed a few inner classes due to conflict when stripping off Walker from their outer classes: ContigStats, FlagStats and FastaStats.
-- Heng wants to use 0x0? to represent any missing type value, which in our implementation was invalid. Updated our codebase to support this construct. Heng said he'll update the BCF2 quick reference.
-- Enabled integration test reading Heng's ex2.bcf file
-- GATK now only warns in the case where the END info field isn't the same (or +1 due to padding) as the getEnd() function as determined by the GATK. Turns out there's a single record in the 1000G SV call set that doesn't have the right length
-- VariantContextTestProvider now tests that X = Y where X -> writing -> reading -> writing -> reading = Y for a variety of variant context inputs X
-- Added integration test reading 1000G SV chr1 calls (from Chris)
-- If eval has genotypes and comp has genotypes, then subset the genotypes of comp down to the samples being evaluated when considering TP, FP, FN, TN status. This is important in the case where you want to use this to assess, for example, the quality of calls on NA12878 but you have a CEU trio comp VCF. The previous version was counting sites polymorphic in mom against the calls in NA12878.
-- Added testdata VCF and integrationtests to ensure this behavior continues in the future
-- TODO: actually run integration tests when I have an internet connection
-- If eval has genotypes and comp has genotypes, then subset the genotypes of comp down to the samples being evaluated when considering TP, FP, FN, TN status. This is important in the case where you want to use this to assess, for example, the quality of calls on NA12878 but you have a CEU trio comp VCF. The previous version was counting sites polymorphic in mom against the calls in NA12878.
-- Added testdata VCF and integrationtests to ensure this behavior continues in the future
-- This actually proved to be a problem with Ion Torrent data where the base quality can be quite low, and so we need to include Q15 bases for calling effectively.
Move the RunReport S3 upload process onto a separate thread with a timeout allowing the parent to continue.
Signed-off-by: Khalid Shakir <kshakir@broadinstitute.org>
* BinaryTag covariate is Experimental, not Standard (this was breaking integration tests)
* New parameter in the Recalibration report requires new MD5 for one of the integration tests.
-- getMetaData now split into getMetaDataInSortedOrder() [old functionality] and getMetaDataInOriginalOrder() [according to the header order]. Important as BCF uses the order of elements in the header in the offsets to keys, and we were automatically sorting the BCF2 header which is out of order in samtools and the whole system was going crazy
-- Updating GATK code to use the appropriate header function (this is why so many files have changed)
-- BCF2 code was busted in not differentiating PASS from . from FILTER in VC (tests coming that will actually stress this)
-- Bugfix for adding contig lines to BCF2 header dictionary
-- VCFHeader metaData no longer sorted internally. The system now maintains the data in header order, and only sorts output as requested in API
-- VCFWriter and BCF2Writer now explictly sort their header lines
-- Don't allow filters to be added that are PASS in the contract
with the new clipping behavior for weird cigars, we no longer can assert the final number of bases in the unit test, so I'm taking this bit off the unit test.
When hard-clipping predict when the read is going to be fully hard clipped to the point where only soft/hard-clips are left in the read and preemptively eliminate the read before the SAMRecord mathematics on malformed cigars kills the GATK.
-- GenotypeBuilder now sorts the list of filter strings so that the output is in a consistent order
-- calculateChromosomeCounts removes the AC/AF fields entirely when there are no alt alleles, to be on VCF spec for A defined info field values
-- Fixed bug in VariantDataManager that this validation mode was intended to detect going forward
-- Still no VariantRecalibrationWalkersIntegrationTest for indels with BCF2 but that's because LowQual is missing from test VCF
-- Bugfix for VCFDiffableReader: don't add null filters to object
-- BCF2Codec uses new VCFAlleleClipper to handle clipping / unclipping of alleles
-- AbstractVCFCodec: decodeLoc uses full decode() [still doesn't decode genotypes] to avoid dangerous code duplication. Refactored code that clipped alleles and determined end position into updateBuilderAllelesAndStop method that uses new VCFAlleleClipper. Fixed bug by ensuring the VCF codec always uses the END field in the INFO when it's provided, not just in the case where the there's a biallelic symbolic allele
-- Brand new home for allele clipping / padding routines in VCFAlleleClipper. Actually documented this code, which results in lots of **** negative comments on the code quality. Eric has promised that he and Ami are going to rethink this code from scratch. Fixed many nasty bugs in here, cleaning up unnecessary branches, etc. Added UnitTests in VCFAlleleClipper that actually test the code full. In the process of testing I discovered lots of edge cases that don't work, and I've commented out failing tests or manually skipped them, noting how this tests need to be fixed. Even introduced some minor optimizations
-- VariantContext: validateAllele was broken in the case where there were mixed symbolic and concrete alleles, failing validation for no reason. Fixed.
-- Added computeEndFromAlleles() function to VariantContextUtils and VariantContextBuilder for convenience calculating where the VC really ends given alleles
--
-- refactored allele clipping / padding code into VCFAlleleClipping class, and added much needed docs and TODOs for methods dev guys
-- Added real unit tests for (some) clipping operations in VCFUtilsUnitTest
-- Previous version was reading the size of the encoded genotypes vector for each genotype. This only worked because I never wrote out genotype field values with > 15 elements. Mauricio's killer DiagnoseTargets VCF uncovered the bug. Unfortunately since symbolic allele clipping is still busted those tests are still diabled
-- GenotypeContext getMaxPloidy was returning -1 in the case where there are no genotypes, but the answer should be 0.
-- They now throw an error, as its really unsafe to write out ./. as a special case in the VCFWriter as occurred previously.
-- Added convenience method in VariantContextUtils.addMissingSamples(vc, allSamples) that returns a complete VC where samples are given ./. Genotype objects
-- This allows us to properly pass tests of creating / writing / reading VCFs and BCFs, which previously differed because the VC from the VCF would actually be different from its original VC
-- Updated UG, UGEngine, GenotypeAndValidateWalker, CombineVariants, and VariantsToVCF to manage the master list of samples they are writing out and addMissingSamples via the VCU function
-- Don't use DP for average interval depth but rather AVG_INTERVAL_DP, which is a float now, not an int
-- Don't add PASS filter value to genotypes, as this is actually considered failing filters in the GATK. Genotype filters should be empty for PASSing sites
Updated HSP to use new padding arguments instead of flank intervals file, plus latest QC evals.
IntervalUtils return unmodifiable lists so that utilities don't mutate the collections.
Added a JavaCommandLineFunction.javaGCThreads option to test reducing java's automatic GC thread allocation based on num cpus.
Added comma to list of characters to convert to underscores in GridEngine job names so that GE JSV doesn't choke on the -N values.
JobRunInfo handles the null done times when jobs crash with strange errors.
-- Previously VCF header lines of count type G assumed that the sample would be diploid.
-- Generalized the code to take a VariantContext and return the right result for G count types by calling into the correct numGenotypes in GenotypeLikelihoods class
-- renamed calcNumGenotypes to numGenotypes, which uses a static cache in the class
-- calcNumGenotypes is private, and is used to build the static cache or to compute on the fly for uncached No. allele / ploidy combinations
-- VariantContext calls into getMaxPloidy in GenotypesContext, which caches the max ploidy among samples
-- Added extensive unit tests that compare A and G type values in genotypes
-- Previous bugfix ensures that header fixing is always on in the GATK by default, even after integration tests that failed and when through the VCFDiffableReader. Updating md5s to reflect this.
-- allowMissingVCFHeaders is now part of -U argument. If you want specifically unsafe VCF processing you need -U LENIENT_VCF_PROCESSING. Updated lots of files to use this
-- LENIENT_VCF_PROCESSING disables on the fly VCF header cleanup. This is now implemented via a member variable, not a class variable, which I believe was changing the GATK behavior during integration tests, causing some files to fail that pass when run as a single test because the header reading behavior was changing depending on previous failures.
-- Just completely wrong.
-- BCF2 shadowBCF now checks that the shadow bcf can be written to avoid /dev/null.bcf problem
-- Added samtools ex2.bcf file for decoding to our integrationtests
* field attributesCanBeModified - a null attributes object can't be modified in its current state
* method makeAttributesModifiable() - initialize a null attributes object to empty
-- Added MLEAC and MLEAF format lines to PoolCallerWalker
-- VariantFiltrationWalker now throws an error when JEXL variables cannot be found (XXX < 0.5) but passes through (albeit with a disgusting warning) when a variable is found but its value is a bad type (AF < 0.5) where AF == [0.04,0.00] at multi-allelic variation
-- Allow values to pass assertEquals in VariantContextTestProvider when one file contains X=[null, null] and the other has X missing
-- Update to 2.1.1 from 2.0
-- VariantFiltrationWalker now allows you to run with type unsafe selects, which all default to false when matching. So "AF < 0.5" works even in the presence of multi-allelics now.
--
-- MLAC and MLAF in PoolCaller now use standard MLE_AC and MLE_AF
-- VCFDiffableReader disables onTheFly fixing of VCF header fields so comparisons are easier when headers are changing
-- Flag fields with FLAG_KEY=0 are parsed as though FLAG_KEY were entirely absent in AbstractVCFCodec to fix bug where FLAG_KEY=0 was being translated into FLAG_KEY in output VCF, making a false flag value a true one
-- Fix the GT field value in VariantContextTestProviders so it isn't fixed 1000s of times during testing
-- Keys whose value is null are put into the VariantContext info attributes now
-- Created public static UnifiedGenotyper.getHeaderInfo that loads UG standard header lines, and use this in tools like PoolCaller
-- Created VCFStandardHeaderLines class that keeps standard header lines in the GATK in a single place. Provides convenient methods to add these to a header, as well as functionality to repair standard lines in incoming VCF headers
-- VCF parsers now automatically repair standard VCF header lines when reading the header
-- Updating integration tests to reflect header changes
-- Created private and public testdata directories (public/testdata and private/testdata). Updated tests to use test
-- SelectHeaders now always updates the header to include the contig lines
-- SelectVariants add UG header lines when in regenotype mode
-- Renamed PHRED_GENOTYPE_LIKELIHOODS_KEY to GENOTYPE_PL_KEY
-- Bugfix in BCF2 to handle lists of null elements (can happen in genotype field values from VCFs)
-- Throw error when VCF has unbounded non-flag values that don't have = value bindings
-- By default we no longer allow writing of BCF2 files without contig lines in the header
-- Moved GENOTYPE_KEY vcf header line to VCFConstants. This general migration and cleanup is on Eric's plate now
-- Updated HC to initialize the annotation engine in an order that allows it to write a proper VCF header. Still doesn't work...
-- Updating integration test files. Moved many more files into public/testdata. Updated their headers to all work correctly with new strict VCF header checking.
-- Bugfix for TandemRepeatAnnotation that must be unbounded not A count type as it provides info for the REF as well as each alt
-- No longer add FALSE values to flag values in VCs in VariantAnnotatorEngine. DB = 0 is never seen in the output VCFs now
-- Fixed bug in VCFDiffableReader that didn't differeniate between "." and "PASS" VC filter status
-- Unconditionally add lowQual Filter to UG output VCF files as this is in some cases (EMIT_ALL_SITES) used when the previous check said it wouldn't be
-- VariantsToVCF now properly writes out the GT FORMAT field
-- BCF2 codec explodes when reading symbolic alleles as I literally cannot figure out how to use the allele clipping code. Eric said he and Ami will clean up this whole piece of instructure
-- Fixed bug in BCF2Codec that wasn't setting the phase field correctly. UnitTested now
-- PASS string now added at the end of the BCF2 dictionary after discussion with Heng
-- Fixed bug where I was writing out all field values as BigEndian. Now everything is LittleEndian.
-- VCFHeader detects the case where a count field has size < 0 (some of our files have count = -1) and throws a UserException
-- Cleaned up unused code
-- Fixed bug in BCF2 string encoder that wasn't handling the case of an empty list of strings for encoding
-- Fixed bug where all samples are no called in a VC, in which case we (like the VCFwriter) write out no called diploid genotypes for all samples
-- We always write the number of genotype samples into the BCF2 nSamples header. How we can have a variable number of samples per record isn't clear to me, as we don't have a map from missing samples to header names...
-- Removed old filtersWereAppliedToContext code in VCF as properly handle unfiltered, filtered, and PASS records internally
-- Fastpath function getDisplayBases() in allele that just gives you the raw bytes[] you'd see for an Allele
-- Genotype fields no longer differentiate between unfiltered, filtered, and PASS values. Genotype objects are all PASS implicitly, or explicitly filtered. We only write out the FT values if at least one sample is filtered. Removed interface functions and cleaned up code
-- Refactored padAllele code from createVariantContextWithPaddedAlleles into the function padAllele so that it actually works. In general, **** NEVER COPY CODE **** if you need to share funcitonality make a function, that's why there were invented!
-- Increased the default number of records to read for DiffObjects to 1M
-- The GATK VCFWriter now enforces by default that all INFO, FILTER, and FORMAT fields be properly defined in the header. This helps avoid some of the low-level errors I saw in SelectVariants. This behavior can be disable in the engine with the --allowMissingVCFHeaders argument
-- Fixed broken annotations in TandemRepeat, which were overwriting AD instead of defining RPA
-- Optimizations to VariantEval, removing some obvious low-hanging fruit all in the subsetting of variants by sample
-- SelectVariants header fixes -- Was defining DP for the info field as a FORMAT field, as for AC, AF, and AN original
-- Performance optimizations in BCF2 codec and writer
-- using arrays not lists for intermediate data structures
-- Create once and reuse an array of GenotypeBuilders for the codec, avoiding reallocating this data structure over and over
-- VCFHeader (which needs a complete rewrite, FYI Eric)
-- Warn and fix on the way flag values with counts > 0
-- GenotypeSampleNames are now stored as a List as they are ordered, and the set iteration was slow. Duplicates are detected once at header creation.
-- Explicitly track FILTER fields for efficient lookup in their own hashmap
-- Automatically add PL field when we see a GL field and no PL field
-- Added get and has methods for INFO, FILTER, and FORMAT fields
-- No longer add AC and AF values to the INFO field when there's no ALT allele
-- Memory efficient comparison of VCF and BCF files for shadow BCF testing. Now there's no (memory) constraint on the size of the files we can compare
-- Because of VCF's limited floating point resolution we can only use 1 sig digit for comparing doubles between BCF and VCF
* Sites with more soft clipped bases than regular will force-trigger a variant region
* No more unclipping/reclipping, RR machinery now handles soft clips natively.
* implemented support for base insertion and base deletion quality scores in synthetic and regular reads.
* GATKSAMRecord clone() now creates a fresh object for temporary attributes if one is present.
note: SAMRecords create a shallow copy of the tempAttribute object which was causing multiple reads (that came from the same read) to have their temporary attributes modified by one another inside reduce reads. Beware, if you're not using GATKSAMRecord!
Eric Banks
Yossi Farjoun
Mark DePristo
Christopher Hartl
David Roazen
Guillermo del Angel
Ryan Poplin
Ami Levy Moonshine
Menachem Fromer
Geraldine Van der Auwera
Mauricio Carneiro
Khalid Shakir
Joel Thibault
Roger Zurawicki
Laurent Francioli
Chris Saunders