To active this feature add '--likelihoodCalculationEngine GraphBased' to the HC command line.
New HC Options (both Advanced and Hidden):
==========================================
--likelihoodCalculationEngine PairHMM/GraphBased/Random (default PairHMM)
Specifies what engine should be used to generate read vs haplotype likelihoods.
PairHMM : standard full-PairHMM approach.
GraphBased : using the assembly graph to accelarate the process.
Random : generate random likelihoods - used for benchmarking purposes only.
--heterogeneousKmerSizeResolution COMBO_MIN/COMBO_MAX/MAX_ONLY/MIN_ONLY (default COMBO_MIN)
It idicates how to merge haplotypes produced using different kmerSizes.
Only has effect when used in combination with (--likelihooCalculationEngine GraphBased)
COMBO_MIN : use the smallest kmerSize with all haplotypes.
COMBO_MAX : use the larger kmerSize with all haplotypes.
MIN_ONLY : use the smallest kmerSize with haplotypes assembled using it.
MAX_ONLY : use the larger kmerSize with haplotypes asembled using it.
Major code changes:
===================
* Introduce multiple likelihood calculation engines (before there was just one).
* Assembly results from different kmerSies are now packed together using the AssemblyResultSet class.
* Added yet another PairHMM implementation with a different API in order to spport
local PairHMM calculations, (e.g. a segment of the read vs a segment of the haplotype).
Major components:
================
* FastLoglessPairHMM: New pair-hmm implemtation using some heuristic to speed up partial PairHMM calculations
* GraphBasedLikelihoodCalculationEngine: delegates onto GraphBasedLikelihoodCalculationEngineInstance the exectution
of the graph-based likelihood approach.
* GraphBasedLikelihoodCalculationEngineInstance: one instance per active-region, implements the graph traversals
to calcualte the likelihoods using the graph as an scafold.
* HaplotypeGraph: haplotype threading graph where build from the assembly haplotypes. This structure is the one
used by GraphBasedLikelihoodCalculationEngineInstance to do its work.
* ReadAnchoring and KmerSequenceGraphMap: contain information as how a read map on the HaplotypeGraph that is
used by GraphBasedLikelihoodCalcuationEngineInstance to do its work.
Remove mergeCommonChains from HaplotypeGraph creation
Fixed bamboo issues with HaplotypeGraphUnitTest
Fixed probrems with HaplotypeCallerIntegrationTest
Fixed issue with GraphLikelihoodVsLoglessAccuracyIntegrationTest
Fixed ReadThreadingLikelihoodCalculationEngine issues
Moved event-block iteration outside GraphBased*EngineInstance
Removed unecessary parameter from ReadAnchoring constructor.
Fixed test problem
Added a bit more documentation to EventBlockSearchEngine
Fixing some private - protected dependency issues
Further refactoring making GraphBased*Instance and HaplotypeGraph slimmer. Addressed last pull request commit comments
Fixed FastLoglessPairHMM public -> protected dependency
Fixed probrem with HaplotypeGraph unit test
Adding Graph-based likelihood ratio calculation to HC
To active this feature add '--likelihoodCalculationEngine GraphBased' to the HC command line.
New HC Options (both Advanced and Hidden):
==========================================
--likelihoodCalculationEngine PairHMM/GraphBased/Random (default PairHMM)
Specifies what engine should be used to generate read vs haplotype likelihoods.
PairHMM : standard full-PairHMM approach.
GraphBased : using the assembly graph to accelarate the process.
Random : generate random likelihoods - used for benchmarking purposes only.
--heterogeneousKmerSizeResolution COMBO_MIN/COMBO_MAX/MAX_ONLY/MIN_ONLY (default COMBO_MIN)
It idicates how to merge haplotypes produced using different kmerSizes.
Only has effect when used in combination with (--likelihooCalculationEngine GraphBased)
COMBO_MIN : use the smallest kmerSize with all haplotypes.
COMBO_MAX : use the larger kmerSize with all haplotypes.
MIN_ONLY : use the smallest kmerSize with haplotypes assembled using it.
MAX_ONLY : use the larger kmerSize with haplotypes asembled using it.
Major code changes:
===================
* Introduce multiple likelihood calculation engines (before there was just one).
* Assembly results from different kmerSies are now packed together using the AssemblyResultSet class.
* Added yet another PairHMM implementation with a different API in order to spport
local PairHMM calculations, (e.g. a segment of the read vs a segment of the haplotype).
Major components:
================
* FastLoglessPairHMM: New pair-hmm implemtation using some heuristic to speed up partial PairHMM calculations
* GraphBasedLikelihoodCalculationEngine: delegates onto GraphBasedLikelihoodCalculationEngineInstance the exectution
of the graph-based likelihood approach.
* GraphBasedLikelihoodCalculationEngineInstance: one instance per active-region, implements the graph traversals
to calcualte the likelihoods using the graph as an scafold.
* HaplotypeGraph: haplotype threading graph where build from the assembly haplotypes. This structure is the one
used by GraphBasedLikelihoodCalculationEngineInstance to do its work.
* ReadAnchoring and KmerSequenceGraphMap: contain information as how a read map on the HaplotypeGraph that is
used by GraphBasedLikelihoodCalcuationEngineInstance to do its work.
Remove mergeCommonChains from HaplotypeGraph creation
Fixed bamboo issues with HaplotypeGraphUnitTest
Fixed probrems with HaplotypeCallerIntegrationTest
Fixed issue with GraphLikelihoodVsLoglessAccuracyIntegrationTest
Fixed ReadThreadingLikelihoodCalculationEngine issues
Moved event-block iteration outside GraphBased*EngineInstance
Removed unecessary parameter from ReadAnchoring constructor.
Fixed test problem
Added a bit more documentation to EventBlockSearchEngine
Fixing some private - protected dependency issues
Further refactoring making GraphBased*Instance and HaplotypeGraph slimmer. Addressed last pull request commit comments
Fixed FastLoglessPairHMM public -> protected dependency
Fixed probrem with HaplotypeGraph unit test
CalculatePosteriors enables the user to calculate genotype likelihood posteriors (and set genotypes accordingly) given one or more panels containing allele counts (for instance, calculating NA12878 genotypes based on 1000G EUR frequencies). The uncertainty in allele frequency is modeled by a Dirichlet distribution (parameters being the observed allele counts across each allele), and the genotype state is modeled by assuming independent draws (Hardy-Weinberg Equilibrium). This leads to the Dirichlet-Multinomial distribution.
Currently this is implemented only for ploidy=2. It should be straightforward to generalize. In addition there's a parameter for "EM" that currently does nothing but throw an exception -- another extension of this method is to run an EM over the Maximum A-Posteriori (MAP) allele count in the input sample as follows:
while not converged:
* AC = [external AC] + [sample AC]
* Prior = DirichletMultinomial[AC]
* Posteriors = [sample GL + Prior]
* sample AC = MLEAC(Posteriors)
This is more useful for large callsets with small panels than for small callsets with large panels -- the latter of these being the more common usecase.
Fully unit tested.
Reviewer (Eric) jumped in to address many of his own comments plus removed public->protected dependencies.
Motivation:
The API was different between the regular PairHMM and the FPGA-implementation
via CnyPairHMM. As a result, the LikelihoodCalculationEngine had
to use account for this. The goal is to change the API to be the same
for all implementations, and make it easier to access.
PairHMM
PairHMM now accepts a list of reads and a map of alleles/haplotpes and returns a PerReadAlleleLikelihoodMap.
Added a new primary method that loops the reads and haplotypes, extracts qualities,
and passes them to the computeReadLikelihoodGivenHaplotypeLog10 method.
Did not alter that method, or its subcompute method, at all.
PairHMM also now handles its own (re)initialization, so users don't have to worry about that.
CnyPairHMM
Added that same new primary access method to this FPGA class.
Method overrides the default implementation in PairHMM. Walks through a list of reads.
Individual-read quals and the full haplotype list are fed to batchAdd(), as before.
However, instead of waiting for every read to get added, and then walking through the reads
again to extract results, we just get the haplotype-results array for each read as soon as it
is generated, and pack it into a perReadAlleleLikelihoodMap for return.
The main access method is now the same no matter whether the FPGA CnyPairHMM is used or not.
LikelihoodCalculationEngine
The functionality to loop through the reads and haplotypes and get individual log10-likelihoods
was moved to the PairHMM, and so removed from here. However, this class does need to retain
the ability to pre-process the reads, and post-process the resulting likelihoods map.
Those features were separated from running the HMM and refactored into their own methods
Commented out the (unused) system for finding best N haplotypes for genotyping.
PairHMMIndelErrorModel
Similar changes were made as to the LCE. However, in this case the haplotypes are modified
based on each individual read, so the read-list we feed into the HMM only has one read.
-- Adding changes to CombineVariants to work with the Reference Model mode of the HaplotypeCaller.
-- Added -combineAnnotations mode to CombineVariants to merge the info field annotations by taking the median
-- Added new StrandBiasBySample genotype annotation for use in computing strand bias from single sample input vcfs
-- Bug fixes to calcGenotypeLikelihoodsOfRefVsAny, used in isActive() as well as the reference model
-- Added active region trimming capabilities to the reference model mode, not perfect yet, turn off with --dontTrimActiveRegions
-- We only realign reads in the reference model if there are non-reference haplotypes, a big time savings
-- We only realign reads in the reference model if the read is informative for a particular haplotype over another
-- GVCF blocks will now track and output the minimum PLs over the block
-- MD5 changes!
-- HC tests: from bug fixes in calcGenotypeLikelihoodsOfRefVsAny
-- GVCF tests: from HC changes above and adding in active region trimming
A new PairHMM implementation for read/haplotype likelihood calculations. Output is the same as the LOGLESS_CACHING version.
Instead of allocating an entire (read x haplotype) matrix for each HMM state, this version stores sub-computations in 1D arrays. It also accesses intersections of the (read x haplotype) alignment in a different order, proceeding over "diagonals" if we think of the alignment as a matrix.
This implementation makes use of haplotype caching. Because arrays are overwritten, it has to explicitly store mid-process information. Knowing where to capture this info requires us to look ahead at the subsequent haplotype to be analyzed. This necessitated a signature change in the primary method for all pairHMM implementations.
We also had to adjust the classes that employ the pairHMM:
LikelihoodCalculationEngine (used by HaplotypeCaller)
PairHMMIndelErrorModel (used by indel genotyping classes)
Made the array version the default in the HaplotypeCaller and the UnifiedArgumentCollection.
The latter affects classes:
ErrorModel
GeneralPloidyIndelGenotypeLikelihoodsCalculationModel
IndelGenotypeLikelihoodsCalculationModel
... all of which use the pairHMM via PairHMMIndelErrorModel
* Refactoring implementations of readHeader(LineReader) -> readActualHeader(LineIterator), including nullary implementations where applicable.
* Galvanizing fo generic types.
* Test fixups, mostly to pass around LineIterators instead of LineReaders.
* New rev of tribble, which incorporates a fix that addresses a problem with TribbleIndexedFeatureReader reading a header twice in some instances.
* New rev of sam, to make AbstractIterator visible (was moved from picard -> sam in Tribble API refactor).
-- Bugfix for BAMs containing reads without real (M,I,D,N) operators. Simply needed to set validation stringency to SILENT in the read. Added a BadCigar filter to the SAMRecord stream anyway
-- Add capture all sites mode to AssessNA12878: will write all sites to the badSites VCF, regardless of whether they are bad. It's useful if you essentially want to annotate a VCF with KB information for later analysis, such as computing ROC curves
-- Add ignore filters mode to AssessNA12878: will as expected treat all sites in the input VCF calls as PASS, even if the site has a FILTER field setting
-- Add minPNonRef argument to AssessNA12878: this will consider a site not called even if the NA12878 genotype is not 0/0 if the PLs are present and the PL for 0/0 isn't greater than this value. It allows us to easily differentiate low confidence non-ref sites obtained via multi-sample calling from highly confident non-ref calls that might be real TP or FPs
Problem
-------
Caching strategy is incompatible with the current sorting of the haplotypes, and is rendering the cache nearly useless.
Before the PairHMM updates, we realized that a lexicographically sorted list of haplotypes would optimize the use of the cache. This was only true until we've added the initial condition to the first row of the deletion matrix, which depends on the length of the haplotype. Because of that, every time the haplotypes differ in length, the cache has to be wiped. A lexicographic sorting of the haplotypes will put different lengths haplotypes clustered together therefore wasting *tons* of re-compute.
Solution
-------
Very simple. Sort the haplotypes by LENGTH and then in lexicographic order.
1. Some minor refactorings and claenup (e.g. removing unused imports) throughout.
2. Updates to the KB assessment functionality:
a. Exclude duplicate reads when checking to see whether there's enough coverage to make a call.
b. Lower the threshold on FS for FPs that would easily be filtered since it's only single sample calling.
3. Make the HC consistent in how it treats the pruning factor. As part of this I removed and archived
the DeBruijn assembler.
4. Improvements to the likelihoods for the HC
a. We now include a "tristate" correction in the PairHMM (just like we do with UG). Basically, we need
to divide e by 3 because the observed base could have come from any of the non-observed alleles.
b. We now correct overlapping read pairs. Note that the fragments are not merged (which we know is
dangerous). Rather, the overlapping bases are just down-weighted so that their quals are not more
than Q20 (or more specifically, half of the phred-scaled PCR error rate); mismatching bases are
turned into Q0s for now.
c. We no longer run contamination removal by default in the UG or HC. The exome tends to have real
sites with off kilter allele balances and we occasionally lose them to contamination removal.
5. Improved the dangling tail merging implementation.
-- Assembly graph building now returns an object that describes whether the graph was successfully built and has variation, was succesfully built but didn't have variation, or truly failed in construction. Fixing an annoying bug where you'd prefectly assembly the sequence into the reference graph, but then return a null graph because of this, and you'd increase your kmer because it null was also used to indicate assembly failure
--
-- Output format looks like:
20 10026072 . T <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:3,0:3:9:0,9,120
20 10026073 . A <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:3,0:3:9:0,9,119
20 10026074 . T <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:3,0:3:9:0,9,121
20 10026075 . T <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:3,0:3:9:0,9,119
20 10026076 . T <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:3,0:3:9:0,9,120
20 10026077 . T <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:3,0:3:9:0,9,120
20 10026078 . C <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:5,0:5:15:0,15,217
20 10026079 . A <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:6,0:6:18:0,18,240
20 10026080 . G <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:6,0:6:18:0,18,268
20 10026081 . T <NON_REF> . . . GT:AD:DP:GQ:PL 0/0:7,0:7:21:0,21,267
We use a symbolic allele to indicate that the site is hom-ref, and because we have an ALT allele we can provide AD and PL field values. Currently these are calculated as ref vs. any non-ref value (mismatch or insertion) but doesn't yet account properly for alignment uncertainty.
-- Can we enabled for single samples with --emitRefConfidence (-ERC).
-- This is accomplished by realigning the each read to its most likley haplotype, and then evaluting the resulting pileups over the active region interval. The realignment is done by the HaplotypeBAMWriter, which now has a generalized interface that lets us provide a ReadDestination object so we can capture the realigned reads
-- Provide access to the more raw LocusIteratorByState constructor so we can more easily make them programmatically without constructing lots of misc. GATK data structures. Moved the NO_DOWNSAMPLING constant from LIBSDownsamplingInfo to LocusIteratorByState so clients can use it without making LIBSDownsamplingInfo a public class.
-- Includes GVCF writer
-- Add 1 mb of WEx data to private/testdata
-- Integration tests for reference model output for WGS and WEx data
-- Emit GQ block information into VCF header for GVCF mode
-- OutputMode from StandardCallerArgumentCollection moved to UnifiedArgumentCollection as its no longer relevant for HC
-- Control max indel size for the reference confidence model from the command line. Increase default to 10
-- Don't use out_mode in HaplotypeCallerComplexAndSymbolicVariantsIntegrationTest
-- Unittests for ReferenceConfidenceModel
-- Unittests for new MathUtils functions
-- The previous code would adapter clip before reverting soft clips, so because we only clip the adapter when it's actually aligned (i.e., not in the soft clips) we were actually not removing bases in the adapter unless at least 1 bp of the adapter was aligned to the reference. Terrible.
-- Removed the broken logic of determining whether a read adaptor is too long.
-- Doesn't require isProperPairFlag to be set for a read to be adapter clipped
-- Update integration tests for new adapter clipping code
Previous fixes and tests only covered trailing soft-clips. Now that up front
hard-clipping is working properly though, we were failing on those in the tool.
Added a patch for this as well as a separate test independent of the soft-clips
to make sure that it's working properly.
-- Previous version emitted command lines that look like:
##HaplotypeCaller="analysis_type=HaplotypeCaller input_file=[private/testdata/reduced.readNotFullySpanningDeletion.bam] ..."
the new version provides additional information on when the GATK was run and the GATK version in a nicer format:
##GATKCommandLine=<ID=HaplotypeCaller,Version=2.5-206-gbc7be2b,Date="Thu Jun 20 11:09:01 EDT 2013",Epoch=1371740941197,CommandLineOptions="analysis_type=HaplotypeCaller input_file=[private/testdata/reduced.readNotFullySpanningDeletion.bam] read_buffer_size=null phone_home=AWS ...">
-- Additionally, the command line options are emitted sequentially in the file, so you can see a running record of how a VCF was produced, such as this example from the integration test:
##GATKCommandLine=<ID=HaplotypeCaller,Version=2.5-206-gbc7be2b,Date="Thu Jun 20 11:09:01 EDT 2013",Epoch=1371740941197,CommandLineOptions="lots of stuff">
##GATKCommandLine=<ID=SelectVariants,Version=2.5-206-gbc7be2b,Date="Thu Jun 20 11:16:23 EDT 2013",Epoch=1371741383277,CommandLineOptions="lots of stuff">
-- Removed the ProtectedEngineFeaturesIntegrationTest
-- Actual unit tests for these features!
Improved AnalyzeCovariates (AC) integration test.
Renamed AC test files ending with .grp to .table
Implementation:
* Removed RECAL_PDF/CSV_FILE from RecalibrationArgumentCollection (RAC). Updated rest of the code accordingly.
* Fixed BQSRIntegrationTest to work with new changes
Implemtation details:
* Added tool class *.AnalyzeCovariates
* Added convenient addAll method to Utils to be able to add elements of an array.
* Added parameter comparison methods to RecalibrationArgumentCollection class in order to verify that multiple imput recalibration report are compatible and comparable.
* Modified the BQSR.R script to handle up to 3 different recalibration tables (-BQSR, -before and -after) and removed some irrelevant arguments (or argument values) from the output.
* Added an integration test class.
-WalkerTest now deletes *.idx files on exit
-ArtificialBAMBuilder now deletes *.bai files on exit
-VariantsToBinaryPed walker now deletes its temp files on exit
Problem:
Classes in com.sun.javadoc.* are non-standard. Since we can't depend on their availability for
all users, the GATK proper should not have any runtime dependencies on this package.
Solution:
-Isolate com.sun.javadoc.* dependencies in a DocletUtils class for use only by doclets. The
only users who need to run our doclets are those who compile from source, and they
should be competent enough to figure out how to resolve a missing com.sun.* dependency.
-HelpUtils now contains no com.sun.javadoc.* dependencies and can be safely used by walkers/other
tools.
-Added comments with instructions on when it is safe to use DocletUtils vs. HelpUtils
[delivers #51450385]
[delivers #50387199]
-- Now table looks like:
Name VariantType AssessmentType Count
variant SNPS TRUE_POSITIVE 1220
variant SNPS FALSE_POSITIVE 0
variant SNPS FALSE_NEGATIVE 1
variant SNPS TRUE_NEGATIVE 150
variant SNPS CALLED_NOT_IN_DB_AT_ALL 0
variant SNPS HET_CONCORDANCE 100.00
variant SNPS HOMVAR_CONCORDANCE 99.63
variant INDELS TRUE_POSITIVE 273
variant INDELS FALSE_POSITIVE 0
variant INDELS FALSE_NEGATIVE 15
variant INDELS TRUE_NEGATIVE 79
variant INDELS CALLED_NOT_IN_DB_AT_ALL 2
variant INDELS HET_CONCORDANCE 98.67
variant INDELS HOMVAR_CONCORDANCE 89.58
-- Rewrite / refactored parts of subsetDiploidAlleles in GATKVariantContextUtils to have a BEST_MATCH assignment method that does it's best to simply match the genotype after subsetting to a set of alleles. So if the original GT was A/B and you subset to A/B it remains A/B but if you subset to A/C you get A/A. This means that het-alt B/C genotypes become A/B and A/C when subsetting to bi-allelics which is the convention in the KB. Add lots of unit tests for this functions (from 0 previously)
-- BadSites in Assessment now emits TP sites with discordant genotypes with the type GENOTYPE_DISCORDANCE and tags the expected genotype in the info field as ExpectedGenotype, such as this record:
20 10769255 . A ATGTG 165.73 . ExpectedGenotype=HOM_VAR;SupportingCallsets=ebanks,depristo,CEUTrio_best_practices;WHY=GENOTYPE_DISCORDANCE GT:AD:DP:GQ:PL 0/1:1,9:10:6:360,0,6
Indicating that the call was a HET but the expected result was HOM_VAR
-- Forbid subsetting of diploid genotypes to just a single allele.
-- Added subsetToRef as a separate specific function. Use that in the DiploidExactAFCalc in the case that you need to reduce yourself to ref only. Preserves DP in the genotype field when this is possible, so a few integration tests have changed for the UG
Problem:
-Downsamplers were treating reduced reads the same as normal reads,
with occasionally catastrophic results on variant calling when an
entire reduced read happened to get eliminated.
Solution:
-Since reduced reads lack the information we need to do position-based
downsampling on them, best available option for now is to simply
exempt all reduced reads from elimination during downsampling.
Details:
-Add generic capability of exempting items from elimination to
the Downsampler interface via new doNotDiscardItem() method.
Default inherited version of this method exempts all reduced reads
(or objects encapsulating reduced reads) from elimination.
-Switch from interfaces to abstract classes to facilitate this change,
and do some minor refactoring of the Downsampler interface (push
implementation of some methods into the abstract classes, improve
names of the confusing clear() and reset() methods).
-Rewrite TAROrderedReadCache. This class was incorrectly relying
on the ReservoirDownsampler to preserve the relative ordering of
items in some circumstances, which was behavior not guaranteed by
the API and only happened to work due to implementation details
which no longer apply. Restructured this class around the assumption
that the ReservoirDownsampler will not preserve relative ordering
at all.
-Add disclaimer to description of -dcov argument explaining that
coverage targets are approximate goals that will not always be
precisely met.
-Unit tests for all individual downsamplers to verify that reduced
reads are exempted from elimination
We now run Smith-Waterman on the dangling tail against the corresponding reference tail.
If we can generate a reasonable, low entropy alignment then we trigger the merge to the
reference path; otherwise we abort. Also, we put in a check for low-complexity of graphs
and don't let those pass through.
Added tests for this implementation that checks exact SW results and correct edges added.
-- Variants will be considered matching if they have the same reference allele and at least 1 common alternative allele. This matching algorithm determines how rsID are added back into the VariantContext we want to annotate, and as well determining the overlap FLAG attribute field.
-- Updated VariantAnnotator and VariantsToVCF to use this class, removing its old stale implementation
-- Added unit tests for this VariantOverlapAnnotator class
-- Removed GATKVCFUtils.rsIDOfFirstRealVariant as this is now better to use VariantOverlapAnnotator
-- Now requires strict allele matching, without any option to just use site annotation.
The previous behavior is to process reads with N CIGAR operators as they are despite that many of the tools do not actually support such operator and results become unpredictible.
Now if the there is some read with the N operator, the engine returns a user exception. The error message indicates what is the problem (including the offending read and mapping position) and give a couple of alternatives that the user can take in order to move forward:
a) ask for those reads to be filtered out (with --filter_reads_with_N_cigar or -filterRNC)
b) keep them in as before (with -U ALLOW_N_CIGAR_READS or -U ALL)
Notice that (b) does not have any effect if (a) is enacted; i.e. filtering overrides ignoring.
Implementation:
* Added filterReadsWithMCigar argument to MalformedReadFilter with the corresponding changes in the code to get it to work.
* Added ALLOW_N_CIGAR_READS unsafe flag so that N cigar containing reads can be processed as they are if that is what the user wants.
* Added ReadFilterTest class commont parent for ReadFilter test cases.
* Refactor ReadGroupBlackListFilterUnitTest to extend ReadFilterTest and push up some functionality to that class.
* Modified MalformedReadFilterUnitTest to extend ReadFilterTest and to test the new filter functionality.
* Added AllowNCigarMalformedReadFilterUnittest to check on the behavior when the unsafe ALLOW_N_CIGAR_READS flag is used.
* Added UnsafeNCigarMalformedReadFilterUnittest to check on the behavior when the unsafe ALL flag is used.
* Updated a broken test case in UnifiedGenotyperIntegrationTest resulting from the new behavior.
* Updated EngineFeaturesIntegrationTest testdata to be compliant with new behavior
- Memoized MathUtil's cumulative binomial probability function.
- Reduced the default size of the read name map in reduced reads and handle its resets more efficiently.
-- In the case where we have multiple potential alternative alleles *and* we weren't calling all of them (so that n potential values < n called) we could end up trimming the alleles down which would result in the mismatch between the PerReadAlleleLikelihoodMap alleles and the VariantContext trimmed alleles.
-- Fixed by doing two things (1) moving the trimming code after the annotation call and (2) updating AD annotation to check that the alleles in the VariantContext and the PerReadAlleleLikelihoodMap are concordant, which will stop us from degenerating in the future.
-- delivers [#50897077]
-- This occurred because we were reverting reads with soft clips that would produce reads with negative (or 0) alignment starts. From such reads we could end up with adaptor starts that were negative and that would ultimately produce the "Only one of refStart or refStop must be < 0, not both" error in the FragmentUtils merging code (which would revert and adaptor clip reads).
-- We now hard clip away bases soft clipped reverted bases that fall before the 1-based contig start in revertSoftClippedBases.
-- Replace buggy cigarFromString with proper SAM-JDK call TextCigarCodec.getSingleton().decode(cigarString)
-- Added unit tests for reverting soft clipped bases that create a read before the contig
-- [delivers #50892431]
-- Ultimately this was caused by an underlying bug in the reverting of soft clipped bases in the read clipper. The read clipper would fail to properly set the alignment start for reads that were 100% clipped before reverting, such as 10H2S5H => 10H2M5H. This has been fixed and unit tested.
-- Update 1 ReduceReads MD5, which was due to cases where we were clipping away all of the MATCH part of the read, leaving a cigar like 50H11S and the revert soft clips was failing to properly revert the bases.
-- delivers #50655421
-- Although the original bug report was about SplitSamFile it actually was an engine wide error. The two places in the that provide compression to the BAM write now check the validity of the compress argument via a static method in ReadUtils
-- delivers #49531009
Valentin Ruano-Rubio
Chris Hartl
Geraldine Van der Auwera
bradtaylor
Michael McCowan
MauricioCarneiro
Ryan Poplin
Ami Levy-Moonshine
Eric Banks
Mark DePristo
droazen
sathibault
Scott Thibault