With LegacyLocusIteratorByState deleted, the legacy downsampling implementation
was already non-functional. This commit removes all remaining code in the
engine belonging to the legacy implementation.
-- New algorithm will only try to create an active region if there's at least maxREgionSize + propagation distance states in the list. When that's true, we are guaranteed to actually find a region. So this algorithm is not only truly correct but as super fast, as we only ever do the search for the end of the region when we will certainly find one, and actually generate a region.
-- Helped ID more bugs in the ActivityProfile, necessitating a new algorithm for popping off active regions. This new algorithm requires that at least maxRegionSize + prob. propagation distance states have been examined. This ensures that the incremental results are the same as you get reading in an entire profile and running getRegions on the full profile
-- TODO is to remove incremental search start algorithm, as this is no longer necessary, and nicely eliminates a state variable I was always uncomfortable with
-- Now records the position of the current locus, as well as that of the last read. Necessary when passing through regions with no reads. The previous version would keep accumulating empty active regions, and never discharge them until end of traversal (if there was no reads in the future) or until a read was finally found
-- Protected a call to logger.debug with if ( logger.isDebugEnabled()) to avoid a lot of overhead in writing unseen debugger logging information
-- GATKSAMRecords now cache the result of the getAdapterBoundary, allowing us to avoid repeating a lot of work in LIBS
-- Added unittests to cover adapter clipping
-- This new algorithm is essential to properly handle activity profiles that have many large active regions generated from lots of dense variant events. The new algorithm passes unit tests and passes visualize visual inspection of both running on 1000G and NA12878
-- Misc. commenting of the code
-- Updated ActiveRegionExtension to include a min active region size
-- Renamed ActiveRegionExtension to ActiveRegionTraversalParameters, as it carries more than just the traversal extension now
-- Previously we allowed band pass filter size to be specified along with the sigma. But now that sigma is controllable from walkers and from the command line, we instead compute the filter size given the kernel from the sigma, including all kernel points with p > 1e-5 in the kernel. This means that if you use a smaller kernel you get a small band size and therefore faster ART
-- Update, as discussed with Ryan, the sigma and band size to 17 bp for HC (default ART wide) and max band size of 50 bp
-- Based on the new incremental activity profile
-- Unit Tested! Fixed a few bugs with the old band pass filter
-- Expand IncrementalActivityProfileUnitTest to test the band pass filter as well for basic properties
-- Add new UnitTest for BandPassIncrementalActivityProfile
-- Added normalizeFromRealSpace to MathUtils
-- Cleanup unused code in new activity profiles
-- The incremental version now processes active regions as soon as they are ready to be processed, instead of waiting until the end of the shard as in the previous version. This means that ART walkers will now take much less memory than previously. On chr20 of NA12878 the majority of regions are processed with as few as 500 reads in memory. Over the whole chr20 only 5K reads were ever held in ART at one time.
-- Fixed bug in the way active regions worked with shard boundaries. The new implementation no longer see shard boundaries in any meaningful way, and that uncovered a problem that active regions were always being closed across shard boundaries. This behavior was actually encoded in the unit tests, so those needed to be updated as well.
-- Changed the way that preset regions work in ART. The new contract ensures that you get exactly the regions you requested. the isActive function is still called, but its result has no impact on the regions. With this functionality is should be possible to use the HC as a generic assembly by forcing it to operate over very large regions
-- Added a few misc. useful functions to IncrementalActivityProfile
-- Required before I jump in an redo the entire activity profile so it's can be run imcrementally
-- This restructuring makes the differences between the two functionalities clearer, as almost all of the functionality is in the base class. The only functionality provided by the BandPassActivityProfile is isolated to a finalizeProfile function overloaded from the base class.
-- Renamed ActivityProfileResult to ActivityProfileState, as this is a clearer indication of its actual functionality. Almost all of the misc. walker changes are due to this name update
-- Code cleanup and docs for TraverseActiveRegions
-- Expanded unit tests for ActivityProfile and ActivityProfileState
I've resigned myself instead to create a mapping from Allele to Haplotype. It's cheap so not a big deal, but really shouldn't be necessary.
Ryan and I are talking about refactoring for GATK2.5.
-- UnitTests now include combinational tiling of reads within and spanning shard boundaries
-- ART now properly handles shard transitions, and does so efficiently without requiring hash sets or other collections of reads
-- Updating HC and CountReadsInActiveRegions integration tests
-- Allows us to make a stream of reads or an index BAM file with read having the following properties (coming from n samples, of fixed read length and aligned to the genome with M operator, having N reads per alignment start, skipping N bases between each alignment start, starting at a given alignment start)
-- This stream can be handed back to the caller immediately, or written to an indexed BAM file
-- Update LocusIteratorByStateUnitTest to use this functionality (which was refactored from LIBS unit tests and ArtificialSAMUtils)
Out of curiosity, why does Picard's IndexedFastaSequenceFile allow one to query for start position 0? When doing so, that base is a line feed (-1 offset to the first base in the contig) which is an illegal base (and which caused me no end of trouble)...
Refactored interval specific arguments out of GATKArgumentCollection into InvtervalArgumentCollection such that it can be used in other CommandLinePrograms.
Updated SelectHeaders to print out full interval arguments.
Added RemoteFile.createUrl(Date expiration) to enable creation of presigned URLs for download over http: or file:.
This way walkers won't see anything except the standard bases plus Ns in the reference.
Added option to turn off this feature (to maintain backwards compatibility).
As part of this commit I cleaned up the BaseUtils code by adding a Base enum and removing all of the static indexes for
each of the bases. This uncovered a bug in the way the DepthOfCoverage walker counts deletions (it was counting Ns instead!) that isn't covered by tests. Fortunately that walker is being deprecated soon...
This way, we don't need to create a new Allele for every read/Haplotype pair to be placed in the PerReadAlleleLikelihoodMap (very inefficient). Also, now we can easily get the Haplotype associated with the best allele for a given read.
2. Framework is set up in the VariantAnnotator for the HaplotypeCaller to be able to call in to annotate dbSNP plus comp RODs. Until the HC uses meta data though, this won't work.
-- Run an iterator with 100Ks of reads, each carrying MBs of byte[] data, through LIBS, all starting at the same position. Will crash with an out-of-memory error if we're holding reads anywhere in the system.
-- Is there a better way to test this behavior?
-- Add an option to not allocate always ArrayLists of targetSampleSize, but rather the previous size + MARGIN. This helps for LIBS as most of the time we don't need nearly so much space as we allow
-- consumeFinalizedItems returns an empty list if the reservior is empty, which it often true for our BAM files with low coverage
-- Allow empty sample lists for SamplePartitioner as these are used by the RefTraversals and other non-read based traversals
Make the reservoir downsampler use a linked list, rather than a fixed sized array list, in the expectFewOverflows case
-- Instead of storing a list of list of alignment starts, which is expensive to manipulate, we instead store a linear list of alignment starts. Not grouped as previously. This enables us to simplify iteration and update operations, making them much faster
-- Critically, the downsampler still requires this list of list. We convert back and forth between these two representations as required, which is very rarely for normal data sets (WGS NA12878 on chr20 is 0.2%, 4x WGS is even less).
-- No longer update the total counts in each per-sample state manager, but instead return delta counts that are updated by the overall ReadStateManager
-- One step on the way to improving the underlying representation of the data in PerSampleReadStateManager
-- Make LocusIteratorByState final
-- Use a linked hash map instead of a hash map since we want to iterate through the map fairly often
-- Ensure that we call doneSubmittingReads before getting reads for samples. This function call fell out before and since it wasn't enforced I only noticed the problem while writing comments
-- Don't make unnecessary calls to contains for map. Just use get() and check that the result is null
-- Use a LinkedList in PassThroughDownsampler, since this is faster for add() than the existing ArrayList, and we were's using random access to any resulting
-- Made LIBSPerformance a full featured CommandLineProgram, and it can be used to assess the LIBS performance by reading a provided BAM
-- ReadStateManager now provides a clean interface to iterate in sample order the per-sample read states, allowing us to avoid many map.get calls
-- Moved updateReadStates to ReadStateManager
-- Removed the unnecessary wrapping of an iterator in ReadStateManager
-- readStatesBySample is now a LinkedHashMap so that iteration occurs in LIBS sample order, allowing us to avoid many unnecessary calls to map.get iterating over samples. Now those are just map native iterations
-- Restructured collectPendingReads for simplicity, removing redundant and consolidating common range checks. The new piece is code is much clearer and avoids several unnecessary function calls
-- Only ReadBackedPileupImpl (concrete class) and ReadBackedPileup (interface) live, moved all functionality of AbstractReadBackedPileup into the impl
-- ReadBackedPileupImpl was literally a shell class after we removed extended events. A few bits of code cleanup and we reduced a bunch of class complexity in the gatk
-- ReadBackedPileups no longer accept pre-cached values (size, nMapQ reads, etc) but now lazy load these values as needed
-- Created optimized calculation routines to iterator over all of the reads in the pileup in whatever order is most efficient as well.
-- New LIBS no longer calculates size, n mapq, and n deletion reads while making pileups.
-- Added commons-collections for IteratorChain
-- function to create pileup elements in AlignmentStateMachine and LIBS
-- Cleanup pileup element constructors, directing users to LIBS.createPileupFromRead() that really does the right thing
-- Optimizations to AlignmentStateMachine
-- Properly count deletions. Added unit test for counting routines
-- AlignmentStateMachine.java is no longer recursive
-- Traversals now use new LIBS, not the old one
-- AlignmentStateMachine does what SAMRecordAlignmentState should really do. It's correct in that it's more accurate than the LIB_position tests themselves. This is a non-broken, correct implementation. Needs cleanup, contracts, etc.
-- This version is like 6x slower than the original implementation (according to the google caliper benchmark here). Obvious optimizations for future commit
-- This capability is essential to provide an ordered set of used reads to downstream users of LIBS, such as ART, who want an efficient way to get the reads used in LIBS
-- Vastly expanded the multi-read, multi-sample LIBS unit tests to make sure this capability is working
-- Added createReadStream to ArtificialSAMUtils that makes it relatively easy to create multi-read, multi-sample read streams for testing
-- Split out all of the inner classes of LIBS into separate independent classes
-- Split / add unit tests for many of these components.
-- Radically expand unit tests for SAMRecordAlignmentState (the lowest level piece of code) making sure at least some of it works
-- No need to change unit tests or integration tests. No change in functionality.
-- Added (currently disabled) code to track all submitted reads to LIBS, but this isn't accessible or tested
Instead of the GATK Engine creating a new BaseRecalibrator (not clean), it just keeps track of the arguments (clean).
There are still some dependency issues, but it looks like they are related to Ami's code. Need to look into it further.
-- Added unit tests for combining RecalibrationTables. As a side effect now has serious tests for incrementDatumOrPutIfNecessary
-- Removed unnecessary enum.index system from RecalibrationTables.
-- Moved what were really static utility methods out of RecalibrationEngine and into RecalUtils.
-- Added unit tests for EventType and ReadRecalibrationInfo
-- Simplified interface of EventType. Previously this enum carried an index with it, but this is redundant with the enum.ordinal function. Now just using that function instead.
-- With the newer, faster BQSR, scaling was limited by the NestedIntegerArray. The solution to this is to make the entire table thread-local, so that each nct thread has its own data and doesn't have any collisions.
-- Removed the previous partial solution of having a thread-local quality score table
-- Added a new argument -lowMemory
Ami Levy-Moonshine
Ryan Poplin
Tad Jordan
David Roazen
Mark DePristo
Mauricio Carneiro
Eric Banks
Khalid Shakir
Chris Hartl
Joel Thibault
Chris Hartl