-- This new functionality allows the client to make decisions about how to handle non-informative reads, rather than having a single enforced constant that isn't really appropriate for all users. The previous functionality is maintained now and used by all of the updated pieces of code, except the BAM writers, which now emit reads to display to their best allele, regardless of whether this is particularly informative or not. That way you can see all of your data realigned to the new HC structure, rather than just those that are specifically informative.
-- This all makes me concerned that the informative thresholding isn't appropriately used in the annotations themselves. There are many cases where nearby variation makes specific reads non-informative about one event, due to not being informative about the second. For example, suppose you have two SNPs A/B and C/D that are in the same active region but separated by more than the read length of the reads. All reads would be non-informative as no read provides information about the full combination of 4 haplotypes, as they reads only span a single event. In this case our annotations will all fall apart, returning their default values. Added a JIRA to address this (should be discussed in group meeting)
-- DeBruijnAssembler functions are no longer static. This isn't the right way to unit test your code
-- An a HaplotypeCaller command line option to use low-quality bases in the assembly
-- Refactored DeBruijnGraph and associated libraries into base class
-- Refactored out BaseEdge, BaseGraph, and BaseVertex from DeBruijn equivalents. These DeBruijn versions now inherit from these base classes. Added some reasonable unit tests for the base and Debruijn edges and vertex classes.
-- SeqVertex: allows multiple vertices in the sequence graph to have the same sequence and yet be distinct
-- Further refactoring of DeBruijnAssembler in preparation for the full SeqGraph <-> DeBruijnGraph split
-- Moved generic methods in DeBruijnAssembler into BaseGraph
-- Created a simple SeqGraph that contains SeqVertex objects
-- Simple chain zipper for SeqGraph that reproduces the results for the mergeNode function on DeBruijnGraphs
-- A working version of the diamond remodeling algorithm in SeqGraph that converts graphs that look like A -> Xa, A -> Ya, Xa -> Z, Ya -> Z into A -> X -> a, A -Y -> a, a -> Z
-- Allow SeqGraph zip merging of vertices where the in vertex has multiple incoming edges or the out vertex has multiple outgoing edges
-- Fix all unit tests so they work with the new SeqGraph system. All tests passed without modification.
-- Debugging makes it easier to tell which kmer graph contributes to a haplotype
-- Better docs and unit tests for BaseVertex, SeqVertex, BaseEdge, and KMerErrorCorrector
-- Remove unnecessary printing of cleaning info in BaseGraph
-- Turn off kmer graph creation in DeBruijnAssembler.java
-- Only print SeqGraphs when debugGraphTransformations is set to true
-- Rename DeBruijnGraphUnitTest to SeqGraphUnitTest. Now builds DeBruijnGraph, converts to SeqGraph, uses SeqGraph.mergenodes and tests for equality.
-- Update KBestPathsUnitTest to use SeqGraphs not DebruijnGraphs
-- DebruijnVertex now longer takes kmer argument -- it's implicit that the kmer length is the sequence.length now
-- Added a -dontGenotype mode for testing assembly efficiency
-- However, it looks like this has a very negative impact on the quality of the results, so the code should be deleted
--Based on existing code in GenomeAnalysisEngine
--Hashmaps hold mapping of deprecated tool name to version number and recommended replacement (if any)
--Using FastUtils for maps; specifically Object2ObjectMap but there could be a better type for Strings...
--Added user exception for deprecated annotations
--Added deprecation check to AnnotationInterfaceManager.validateAnnotations
--Run when annotations are initialized
--Made annotation sets instead of lists
--Refactored listAnnotations basic method out of VA into HelpUtils
--HelpUtils.listAnnotations() is now called by both VA and the new ListAnnotations utility (lives in sting.tools)
--This way we keep the VA --list option but we also offer a way to list annotations without a full valid VA command-line, which was a pain users continually complained about
--We could get rid of the VA --list option altogether ...?
-- @Output isn't required for AssessNA12878
-- Previous version would could non-variant sites in NA12878 that resulted from subsetting a multi-sample VC to NA12878 as CALLED_BUT_NOT_IN_DB sites. Now they are properly skipped
-- Bugfix for subsetting samples to NA12878. Previous version wouldn't trim the alleles when subsetting down a multi-sample VCF, so we'd have false FN/FP sites at indels when the multi-sample VCF has alleles that result in the subset for NA12878 having non-trimmed alleles. Fixed and unit tested now.
-- Simply caps PairHMM likelihoods from rising above 0 by taking the min of the likelihood and 0. Will be properly fixed in GATK 2.5 with better PairHMM implementation.
- Moved AverageAltAlleleLength, MappingQualityZeroFraction and TechnologyComposition to Private
- VariantType, TransmissionDisequilibriumTest, MVLikelihoodRatio and GCContent are no longer Experimental
- AlleleBalanceBySample, HardyWeinberg and HomopolymerRun are Experimental and available to users with a big bold caveat message
- Refactored getMeanAltAlleleLength() out of AverageAltAlleleLength into GATKVariantContextUtils in order to make QualByDepth independent of where AverageAltAlleleLength lives
- Unrelated change, bundled in for convenience: made HC argument includeUnmappedreads @Hidden
- Removed unnecessary check in AverageAltAlleleLength
* ClippingOp updated to incorporate Ns in the hard clips.
* ReadUtils.getReadCoordinateForReferenceCoordinate() updated to account for Ns.
* Added test that covers the BQSR case we saw.
* Created GSA-856 (for Mauricio) to add lots of tests to ReadUtils.
* It will require refactoring code and not in the scope of what I was willing to do to fix this.
-- Strandless GATK reads are ones where they don't really have a meaningful strand value, such as Reduced Reads or fragment merged reads. Added GATKSAMRecord support for such reads, along with unit tests
-- The merge overlapping fragments code in FragmentUtils now produces strandless merged fragments
-- FisherStrand annotation generalized to treat strandless as providing 1/2 the representative count for both strands. This means that that merged fragments are properly handled from the HC, so we don't hallucinate fake strand-bias just because we managed to merge a lot of reads together.
-- The previous getReducedCount() wouldn't work if a read was made into a reduced read after getReducedCount() had been called. Added new GATKSAMRecord method setReducedCounts() that does the right thing. Updated SlidingWindow and SyntheticRead to explicitly call this function, and so the readTag parameter is now gone.
-- Update MD5s for change to FS calculation. Differences are just minor updates to the FS
-- Code was undocumented, big, and not well tested. All three things fixed.
-- Currently not passing, but the framework works well for testing
-- Added concat(byte[] ... arrays) to utils
GATK-73 updated docs for bqsr args
GATK-9 differentiate CountRODs from CountRODsByRef
GATK-76 generate GATKDoc for CatVariants
GATK-4 made resource arg required
GATK-10 added -o, some docs to CountMales; some docs to CountLoci
GATK-11 fixed by MC's -o change; straightened out the docs.
GATK-77 fixed references to wiki
GATK-76 Added Ami's doc block
GATK-14 Added note that these annotations can only be used with VariantAnnotator
GATK-15 specified required=false for two arguments
GATK-23 Added documentation block
GATK-33 Added documentation
GATK-34 Added documentation
GATK-32 Corrected arg name and docstring in DiffObjects
GATK-32 Added note to DO doc about reference (required but unused)
GATK-29 Added doc block to CountIntervals
GATK-31 Added @Output PrintStream to enable -o
GATK-35 Touched up docs
GATK-36 Touched up docs, specified verbosity is optional
GATK-60 Corrected GContent annot module location in gatkdocs
GATK-68 touched up docs and arg docstrings
GATK-16 Added note of caution about calling RODRequiringAnnotations as a group
GATK-61 Added run requirements (num samples, min genotype quality)
Tweaked template and generic doc block formatting (h2 to h3 titles)
GATK-62 Added a caveat to HR annot
Made experimental annotation hidden
GATK-75 Added setup info regarding BWA
GATK-22 Clarified some argument requirements
GATK-48 Clarified -G doc comments
GATK-67 Added arg requirement
GATK-58 Added annotation and usage docs
GSATDG-96 Corrected doc
Updated MD5 for DiffObjectsIntegrationTests (only change is link in table title)
* ReadTransformers can say they must be first, must be last, or don't care.
* By default, none of the existing ones care about ordering except BQSR (must be first).
* This addresses a bug reported on the forum where BAQ is incorrectly applied before BQSR.
* The engine now orders the read transformers up front before applying iterators.
* The engine checks for enabled RTs that are not compatible (e.g. both must be first) and blows up (gracefully).
* Added unit tests.
Too many users (with RNASeq reads) are hitting these exceptions that were never supposed to happen. Let's give them (and us) a better and clearer error message.
-- The new code includes a new mode to write out a BAM containing reads realigned to the called haplotypes from the HC, which can be easily visualized in IGV.
-- Previous functionality maintained, with bug fixes
-- Haplotype BAM writing code now lives in utils
-- Created a base class that includes most of the functionality of writing reads realigned to haplotypes onto haplotypes.
-- Created two subclasses, one that writes all haplotypes (previous functionality) and a CalledHaplotypeBAMWriter that will only write reads aligned to the actually called haplotypes
-- Extended PerReadAlleleLikelihoodMap.getMostLikelyAllele to optionally restrict set of alleles to consider best
-- Massive increase in unit tests in AlignmentUtils, along with several new powerful functions for manipulating cigars
-- Fix bug in SWPairwiseAlignment that produces cigar elements with 0 size, and are now fixed with consolidateCigar in AlignmentUtils
-- HaplotypeCaller now tracks the called haplotypes in the GenotypingEngine, and returns this information to the HC for use in visualization.
-- Added extensive docs to HaplotypeCaller on how to use this capability
-- BUGFIX -- don't modify the read bases in GATKSAMRecord in LikelihoodCalculationEngine in the HC
-- Cleaned up SWPairwiseAlignment. Refactored out the big main and supplementary static methods. Added a unit test with a bug TODO to fix what seems to be an edge case bug in SW
-- Integration test to make sure we can actually write a BAM for each mode. This test only ensures that the code runs and doesn't exception out. It doesn't actually enforce any MD5s
-- HaplotypeBAMWriter also left aligns indels in the reads, as SW can return a random placement of a read against the haplotype. Calls leftAlign to make the alignments more clear, with unit test of real read to cover this case
-- Writes out haplotypes for both all haplotype and called haplotype mode
-- Haplotype writers now get the active region call, regardless of whether an actual call was made. Only emitting called haplotypes is moved down to CalledHaplotypeBAMWriter
* Fixed GenomeLocSortedSet.add() to ensure that overlapping intervals are detected and an exception is thrown.
* Fixed GenomeLocSortedSet.addRegion() by merging it with the add() method; it now produces sorted inputs in all cases.
* Cleaned up duplicated code throughout the engine to create a list of intervals over all contigs.
* Added more unit tests for add functionality of GLSS.
* Resolves GSA-775.
-- Refactor initialization routine into BadSitesWriter. This now adds the GQ and DP genotype header lines which are necessarily if the input VCF doesn't have proper headers
-- GATKVariantContextUtils subset to biallelics now tolerates samples with bad GL values for multi-allelics, where it just removes the PLs and issues a warning.
* Split the cases into reads that don't have a RG at all vs. those with a RG that's not defined in the header.
* Added integration tests to make sure that the correct error is thrown.
* Resolved GSA-407.
* Removed from codebase NestedHashMap since it is unused and untested.
* Integration tests change because the BQSR CSV is now sorted automatically.
* Resolves GSA-732
-- This is done to take advantage of longer reads which can produce less ambiguous haplotypes
-- Integration tests change for HC and BiasedDownsampling
The GATK engine does not behave correctly when contigs are indexed
differently in the reads sequence dictionaries vs. the reference
sequence dictionary, and the inconsistently-indexed contigs are included
in the user's intervals. For example, given the dictionaries:
Reference dictionary = { chrM, chr1, chr2, ... }
BAM dictionary = { chr1, chr2, ... }
and the interval "-L chr1", the engine would fail to correctly retrieve
the reads from chr1, since chr1 has a different index in the two dictionaries.
With this patch, we throw an exception if there are contig index differences
between the dictionaries for reads and reference, AND the user's intervals
include at least one of the mismatching contigs.
The user can disable this exception via -U ALLOW_SEQ_DICT_INCOMPATIBILITY
In all other cases, dictionary validation behaves as before.
I also added comprehensive unit tests for the (previously-untested)
SequenceDictionaryUtils class.
GSA-768 #resolve
-- Instead of doing a full SW alignment against the reference we read off bubbles from the assembly graph.
-- Smith-Waterman is run only on the base composition of the bubbles which drastically reduces runtime.
-- Refactoring graph functions into a new DeBruijnAssemblyGraph class.
-- Bug fix in path.getBases().
-- Adding validation code to the assembly engine.
-- Renaming SimpleDeBruijnAssembler to match the naming of the new Assembly graph class.
-- Adding bug fixes, docs and unit tests for DeBruijnAssemblyGraph and KBestPaths classes.
-- Added ability to ignore bubbles that are too divergent from the reference
-- Max kmer can't be bigger than the extension size.
-- Reverse the order that we create the assembly graphs so that the bigger kmers are used first.
-- New algorithm for determining unassembled insertions based on the bubble traversal instead of the full SW alignment.
-- Don't need the full read span reference loc for anything any more now that we clip down to the extended loc for both assembly and likelihood evaluation.
-- Updating HaplotypeCaller and BiasedDownsampling integration tests.
-- Rebased everything into one commit as requested by Eric
-- improvements to the bubble traversal are coming as a separate push
-- AssessNA12878 now breaks out multi-allelics into bi-allelic components. This means that we can properly assess multi-allelic calls against the bi-allelic KB
-- Refactor AssessNA12878, moving into assess package in KB. Split out previously private classes in the walker itself into separate classes. Added real docs for all of the classes.
-- Vastly expand (from 0) unit tests for NA12878 assessments
-- Allow sites only VCs to be evaluated by Assessor
-- Move utility for creating simple VCs from a list of string alleles from GATKVariantContextUtilsUnitTest to GATKVariantContextUtils
-- Assessor bugfix for discordant records at a site. Previous version didn't handle properly the case where one had a non-matching call in the callset w.r.t. the KB, so that the KB element was eaten during the analysis. Fixed. UnitTested
-- See GSA-781 -- Handle multi-allelic variants in KB for more information
-- Bugfix for missing site counting in AssessNA12878. Previous version would count N misses for every missed value at a site. Not that this has much impact but it's worth fixing
-- UnitTests for BadSitesWriter
-- UnitTests for filtered and filtering sites in the Assessor
-- Cleanup end report generation code (simply the code). Note that instead of "indel" the new code will print out "INDELS"
-- Assessor DoC calculations now us LIBS and RBPs for the depth calculation. The previous version was broken for reduced reads. Added unit test that reads a complex reduced read example and matches the DoC of this BAM with the output of the GATK DoC tool here.
-- Added convenience constructor for LIBS using just SAMFileReader and an iterator. It's now easy to create a LIBS from a BAM at a locus. Added advanceToLocus function that moves the LIBS to a specific position. UnitTested via the assessor (which isn't ideal, but is a proper test)
-- Now supports trimming the alleles from both the reverse and forward direction.
-- Added lots of unit tests for forwrad allele trimming, as well as creating VC from forward and reverse trimming.
-- Added docs and tests for the code, to bring it up to GATK spec
These 2 changes improve runtime performance almost as much as Ryan's previous attempt (with ID-based comparisons):
* Don't unnecessarily overload Allele.getBases() in the Haplotype class.
* Haplotype.getBases() was calling clone() on the byte array.
* Added a constructor to Allele (and Haplotype) that takes in an Allele as input.
* It makes a copy of he given allele without having to go through the validation of the bases (since the Allele has already been validated).
* Rev'ed the variant jar accordingly.
For the reviewer: all tests passed before rebasing, so this should be good to go as far as correctness.
-- top-level walker type (locus, read etc)
-- parallelism options (nt or nct)
-- annotation type (for Variant Annotations)
-- downsampling settings that override engine defaults
-- reference window size
-- active region settings
-- partitionBy info
-- Added getClazzAnnotations() as hub to retrieve various annotations values and class properties through reflection
-- Added getReadFilters() method to retrieve Read Filter annotations
-- getReadFilters() uses recursion to walk up the inheritance to also capture superclass annotations
-- getClazzAnnotations() stores collected info in doc handler root, which is unit.forTemplate in Doclet
-- Modified FreeMarker template to use the Readfilters info (displayed after arg table, before additional capabilities)
-- Tadaaa :-) #GSATDG-63 resolve
-- modified ReadBin GenomeLoc to keep track of softStart() and softEnd() of the reads coming in, to make sure the reference will always be sufficient even if we want to use the soft-clipped bases
-- changed the verification from readLength to aligned bases to allow reads with soft-clipped bases
-- switched TreeSet -> PriorityQueue in the ConstrainedMateFixer as some different reads can be considered equal by picard's SAMRecordCoordinateComparator (the Set was replacing them)
-- pulled out ReadBin class so it can be testable
-- added unit tests for ReadBin with soft-clips
-- added tests for getMismatchCount (AlignmentUtils) to make sure it works with soft-clipped reads
GSA-774 #resolve
-- added a logger.error with a more descriptive message of what the most likely cause of the error is
Typical error happens when a walker's global variable is not initialized properly (usually in test conditions). The old error message was very hard to understand "Could not create module because of an exception of type NullPointerException ocurred caused by exception null"
-- Active regions are created as normal, but they are split and trimmed to the engine intervals when added to the traversal, if there are intervals present.
-- UnitTests for ActiveRegion.splitAndTrimToIntervals
-- GenomeLocSortedSet.getOverlapping uses binary search to efficiently in ~ log N time find overlapping intervals
-- UnitTesting overlap function in GenomeLocSortedSet
-- Discovered fundamental implementation bug in that adding genome locs out of order (elements on 20 then on 19) produces an invalid GenomeLocSortedSet. Created a JIRA to address this: https://jira.broadinstitute.org/browse/GSA-775
-- Constructor that takes a collection of genome locs now sorts its input and merges overlapping intervals
-- Added docs for the constructors in GLSS
-- Update HaplotypeCaller MD5s, which change because ActiveRegions are now restricted to the engine intervals, which changes slightly the regions in the tests and so the reads in the regions, and thus the md5s
-- GenomeAnalysisEngineUnitTest needs to provide non-null genome loc parser
-- log10 functions in QualityUtils allow -Infinity to allow log10(0.0) values
-- Fix edge condition of log10OneMinusX failing with Double.MIN_VALUE
-- Fix another edge condition of log10OneMinusX failing with a small but not min_value double
-- The UG was using MathUtils binomial probability backward, so that the estimated confidence was always NaN, and was as a side effect other utils converted this to a meaningless 0.0. This is all because there wasn't a unit test.
-- I've fixed the calculation, so it's now log10 based, uses robust MathUtils and QualityUtils functions to compute probabilities, and added a unit test.
-- Fixed a few conversion bugs with edge case quals (ones that were very high)
-- Fixed a critical bug in the conversion of quals that was causing near capped quals to fall below their actual value. Will undoubtedly need to fix md5s
-- More precise prob -> qual calculations for very high confidence events in phredScaleCorrectRate, trueProbToQual, and errorProbToQual. Very likely to improve accuracy of many calculations in the GATK
-- Added errorProbToQual and trueProbToQual calculations that accept an integer cap, and perform the (tricky) conversion from int to byte correctly.
-- Full docs and unit tests for phredScaleCorrectRate and phredScaleErrorRate.
-- Renamed probToQual to trueProbToQual
-- Added goodProbability and log10OneMinusX to MathUtils
-- Went through the GATK and cleaned up many uses of QualityUtils
-- Cleanup constants in QualityUtils
-- Added full docs for all of the constants
-- Rename MAX_QUAL_SCORE to MAX_SAM_QUAL_SCORE for clarity
-- Moved MAX_GATK_USABLE_Q_SCORE to RecalDatum, as it's s BQSR specific feature
-- Convert uses of QualityUtils.errorProbToQual(1-x) to QualityUtils.trueProbToQual(x)
-- Cleanup duplicate quality score routines in MathUtils. Moved and renamed MathUtils.log10ProbabilityToPhredScale => QualityUtils.phredScaleLog10ErrorRate. Removed 3 routines from MathUtils, and remapped their usages into the better routines in QualityUtils
Mark DePristo
Geraldine Van der Auwera
MauricioCarneiro
Ryan Poplin
Eric Banks
David Roazen