For now, the het reduction should only be performed for diploids (n=2). We haven't really tested it for other ploidy so it should remain hidden until someone braves it out.
-- Updating integration tests, confirming that results for the original EXACT model are as expected given our new more rigorous application of likelihoods, priors, and posteriors
-- Fix basic logic bug in AFCalcResult.isPolymorphic and UnifiedGenotypeEngine, where isNonRef really meant isRef. Not ideal. Finally caught by some tests, but good god it almost made it into the code
-- Now takes the Math.abs of the phred-scaled confidence so that we don't see -0.0
-- Massive new suite of unit tests to ensure that bi-allelic and tri-allele events are called properly with all models, and that the IndependentAllelesDiploidExactAFCalc calls events with up to 4 alt alleles correctly. ID'd some of the bugs below
-- Fix sort order bug in IndependentAllelesDiploidExactAFCalc caught by new unit tests
-- Fix bug in GeneralPloidyExactAFCalc where the AFCalcResult has meaningless values in the likelihoods when no there we no informative GLs.
-- New capabilities in IndependentAllelesDiploidExactAFCalc to actually apply correct theta^n.alt.allele prior.
-- Tests that theta^n.alt.alleles is being applied correctly
-- Bugfix: keep in logspace when computing posterior probability in toAFCalcResult in AFCalcResultTracker.java
-- Bugfix: use only the alleles used in genotyping when assessing if an allele is polymorphic in a sample in UnifiedGenotyperEngine
-- AFCalcFactory is the only way to make AFCalcs now. There's a nice ordered enum there describing the models and their ploidy and max alt allele restrictions. The factory makes it easy to create them, and to find models that work for you given your ploidy and max alt alleles.
-- AFCalc no longer has UAC constructor -- only AFCalcFactory does. Code cleanup throughout
-- Enabling more unit tests, all of which almost pass now (except for IndependentAllelesDiploidExactAFCalc which will be fixed next)
-- It's now possible to run the UG / HC with any of the exact models currently in the system.
-- Code cleanup throughout the system, reorganizing the unit tests in particular
-- Continuing to get IndependentAllelesDiploidExactAFCalc working correctly. A long way towards the right answer now, but still not there
-- Restored (but not tested) OriginalDiploidExactAFCalc, the clean diploid O(N) version for Ryan
-- MathUtils.normalizeFromLog10 no longer returns -Infinity when kept in log space, enforces the min log10 value there
-- New convenience method in VariantContext that looks up the allele index in the alleles
-- AFCalcResult now sports a isPolymorphic and getLog10PosteriorAFGt0ForAllele functions that allow you to ask individually whether specific alleles we've tried to genotype are polymorphic given some confidence threshold
-- Lots of contracts for AFCalcResult
-- Slowly killing off AFCalcResultsTracker
-- Fix for the way UG checks for alt alleles being polymorphic, which is now properly conditioned on the alt allele
-- Change in behavior for normalizeFromLog10 in MathUtils: now sets the log10 for 0 values to -10000, instead of -Infinity, since this is really better to ensure that we don't have -Infinity values traveling around the system
-- ExactAFCalculationModelUnitTest now checks for meaningful pNonRef values for each allele, uncovering a bug in the GeneralPloidy (not fixed, related to Eric's summation issue from long ago that was reverted) in that we get different results for diploid and general-ploidy == 2 models for multi-allelics.
-- All of the code now uses the AFCalc object, not the not package protected AFCalcResultTracker. Nearly all unit tests pass (expect for a contract failing one that will be dealt with in subsequent commit), due to -Infinity values from normalizeLog10.
-- Changed the way that UnifiedGenotyper decides if the best model is non-ref. Previously looked at the MAP AC, but the MAP AC values are no longer provided by AFCalcResult. This is on purpose, because the MAP isn't a meaningful quantity for the exact model (i.e., everything is going to go to MLE AC in some upcoming commit). If you want to understand why come talk to me. Now uses the isPolymorphic function and the EMIT confidence, so that if pNonRef > EMIT then the site is poly, otherwise it's mono.
-- Renamed old class AFCalcResultTracker. This object is now allocated by the AFCalc itself, since it is heavy-weight and was badly optimized in the UG with a thread-local variable. Now, since there's already a AFCalc thread-local there, we get that optimization for free.
-- Removed the interface to provide the AFCalcResultTracker to getlog10PNonRef.
-- Wrote new, clean but unused AFCalcResult object that will soon replace the tracker as the external interface to the AFCalc model results, leaving the tracker as an internal tracker structure. This will allow me to (1) finally test things exhaustively, as the contracts on this class are clear (2) finalize the IndependentAllelesDiploidExactAFCalc class as it can work with a meaningfully defined result across each object
-- This model separates each of N alt alleles, combines the genotype likelihoods into the X/X, X/N_i, and N_i/N_i biallelic case, and runs the exact model on each independently to handle the multi-allelic case. This is very fast, scaling at O(n.alt.alleles x n.samples)
-- Many outstanding TODOs in order to truly pass unit tests
-- Added proper unit tests for the pNonRef calculation, which all of the models pass
-- Now contained in a package called afcalc
-- Extracted standard alone classes from private static classes in ExactAF
-- Most fields are now private, with accessors
-- Overall cleaner organization now
-- Now there's no duplication between exact old and constrained models. The behavior is controlled by an overloaded abstract function
-- No more static function to access the linear exact model -- you have to create the surrounding class. Updated code in the system
-- Everything passes unit tests
-- walks over the genotypes in VC, and computes for each alt allele the maximum AC we need to consider in that alt allele dimension. Does the calculation based on the PLs in each genotype g, choosing to update the max AC for the alt alleles corresponding to that PL. Only takes the first lowest PL, if there are multiple genotype configurations with the same PL value. It takes values in the order of the alt alleles.
-- 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
-- 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)
-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.
-- 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
-- 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
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
-- 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
-- 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.
* 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.
Mauricio Carneiro
Ryan Poplin
Mark DePristo
Guillermo del Angel
Eric Banks
Yossi Farjoun
David Roazen