This bug will happen in all adapter/wrapper classes that are passed a resource, and then in their close method they ignore requests to close the wrapped resource, causing a leak when the adapter is the only one left with a reference to the resource.
Ex:
public Wrapper getNewWrapper(File path) {
FileStream myStream = new FileStream(path); // This stream must be eventually closed.
return new Wrapper(myStream);
}
public void close(Wrapper wrapper) {
wrapper.close(); // If wrapper.close() does nothing, NO ONE else has a reference to close myStream.
}
The practical differences between version 1.0 and this one (v1.1) are:
* the underlying data structure now uses arrays instead of hashes, which should drastically reduce the memory overhead required to create large tables.
* no more primary keys; you can still create arbitrary IDs to index into rows, but there is no special cased primary key column in the table.
* no more dangerous/ugly table operations supported except to increment a cell's value (if an int) or to concatenate 2 tables.
Integration tests change because table headers are different.
Old classes are still lying around. Will clean those up in a subsequent commit.
From tribble logs:
Binary feature support in tribble
-- Massive refactoring and cleanup
-- Many bug fixes throughout
-- FeatureCodec is now general, with decode etc. taking a PositionBufferedStream
as an argument not a String
-- See ExampleBinaryCodec for an example binary codec
-- AbstractAsciiFeatureCodec provides to its subclass the same String decode,
readHeader functionality before. Old ASCII codecs should inherit from this base
class, and will work without additional modifications
-- Split AsciiLineReader into a position tracking stream
(PositionalBufferedStream). The new AsciiLineReader takes as an argument a
PositionalBufferedStream and provides the readLine() functionality of before.
Could potentially use optimizations (its a TODO in the code)
-- The Positional interface includes some more functionality that's now
necessary to support the more general decoding of binary features
-- FeatureReaders now work using the general FeatureCodec interface, so they can
index binary features
-- Bugfixes to LinearIndexCreator off by 1 error in setting the end block
position
-- Deleted VariantType, since this wasn't used anywhere and it's a particularly
clean why of thinking about the problem
-- Moved DiploidGenotype, which is specific to Gelitext, to the gelitext package
-- TabixReader requires an AsciiFeatureCodec as it's currently only implemented
to handle line oriented records
-- Renamed AsciiFeatureReader to TribbleIndexedFeatureReader now that it handles
Ascii and binary features
-- Removed unused functions here and there as encountered
-- Fixed build.xml to be truly headless
-- FeatureCodec readHeader returns a FeatureCodecHeader obtain that contains a
value and the position in the file where the header ends (not inclusive).
TribbleReaders now skip the header if the position is set, so its no longer
necessary, if one implements the general readHeader(PositionalBufferedStream)
version to see header lines in the decode functions. Necessary for binary
codecs but a nice side benefit for ascii codecs as well
-- Cleaned up the IndexFactory interface so there's a truly general createIndex
function that takes the enumerated index type. Added a writeIndex() function
that writes an index to disk.
-- Vastly expanded the index unit tests and reader tests to really test linear,
interval, and tabix indexed files. Updated test.bed, and created a tabix
version of it as well.
-- Significant BinaryFeaturesTest suite.
-- Some test files have indent changes
-- Other tribble contributors did major refactoring / simplification of tribble, which required some changes to GATK code
-- Integrationtests pass without modification, though some very old index files (callable loci beds) were apparently corrupt and no longer tolerated by the newer tribble codebase
Updated ReadFilter abstract class to implement (via UnsupportedOperationException) the new SamRecordFilter.filterOut().
In IndelRealignerIntegrationTest updates for Picard fixes to SAMRecord.getInferredInsertSize() in svn r1115 & r1124.
- Ran FixMates to create new input BAM since running IR with variable maxReadsInMemory means all reads weren't realigned leading to different outputs.
- Updated md5s to match new expectations after looking at TLEN diff engine output.
a) Add ability for ErrorModel to be specified by external log-probability vector for testing.
b) For a given depth and ploidy(=2*samples/pool), create artificial high quality pileup testing from AC=0 to AC=ploidy, and test that pool GL's have expected content.Misc. refactorings and cleanups
c) Misc. cleanups and beautification.
a) Utility class called Probability Vector that holds a log-probability vector and has the ability to clip ends that deviate largely from max value.
b) Used this class to hold site error model, since likelihoods of error model away from peak are so far down that it's not worth computing with them and just wastes time.
c) Expand unit tests and add an exhaustive test for ErrorModel class.
d) Corrected major math bug in ErrorModel uncovered by exhaustive test: log(e^x) is NOT x if log's base = 10.
e) Refactored utility functions that created artificial pileups for testing into separate class ArtificialPileupTestProvider. Right now functionality is limited (one artificial contig of 10 bp), can only specify pileups in one position with a given number of matches and mismatches to ref) but functionality will be expanded in future to cover more test cases.
f) Use this utility class for IndelGenotypeLikelihoods unit test and for PoolGenotypeLikelihoods unit test (the latter testing functionality still not done).
g) Linearized implementation of biallelic exact model (very simple approach, similar to diploid exact model, just abort if we're past the max value of AC distribution and below a threshold). Still need to add unit tests for this and to expand to multiallelic model.
h) Update integration test md5's due to minor differences stemming from linearized exact model and better error model math
The GATK -L unmapped is for GenomeLocs with SAMRecord.NO_ALIGNMENT_REFERENCE_NAME, not SAMRecord.getReadUnmappedFlag()
Previously unmapped flag reads in the last bin were being printed while also seeking for the reads without a reference contig.
* fixed queue script plot file names
* updated the ReadGroupCovariate to use the platform unit instead of sample + lane.
* fixed plotting of marginalized reported qualities
* updated BQSR queue script for faster turnaround
* implemented plot generation for scatter/gatherered runs
* adjusted output file names to be cooperative with the queue script
* added the recalibration report file to the argument table in the report
* added ReadCovariates unit test -- guarantees that all the covariates are being generated for every base in the read
* added RecalibrationReport unit test -- guarantees the integrity of the delta tables
* fixed context covariate famous "off by one" error
* reduced maximum quality score to Q50 (following Eric/Ryan's suggestion)
* remove context downsampling in BQSR R script
This test brings together the old and the new BQSR, building a recalibration table using the two separate frameworks and performing the recalibration calculation using the two different frameworks for 10,000+ bases and asserting that the calculations match in every case.
* Refactored CycleCovariate to be a fragment covariate instead of a per read covariate
* Refactored the CycleCovariateUnitTest to test the pairing information
* Updated BQSR Integration tests accordingly
* Made quantization levels parameter not hidden anymore
* Added hidden option to keep intermediate plotting files for debug purposes (they're automatically deleted)
* Added hidden option not to generate the plots automatically (important for scatter/gathering)
* removed low quality bases from the recalibration report.
* refactored the Datum (Recal and Accuracy) class structure
* created a new plotting csv table for optimized performance with the R script
* added a datum object that carries the accuracy information (AccuracyDatum) for plotting
* added mean reported quality score to all covariates
* added QualityScore as a covariate for plotting purposes
* added unit test to the key manager to operate with one required covariate and multiple optional covariates
* integrated the plotting into BQSR (automatically generates the pdf with the recalibration tearsheet)
- By porting from jython to java now accessible to Queue via automatic extension generation.
- Better handling for problematic sample names by using PicardAggregationUtils.
GATKReportTable looks up keys using arrays instead of dot-separated strings, which is useful when a sample has a period in the name.
CombineVariants has option to suppress the header with the command line, which is now invoked during VCF gathering.
Added SelectHeaders walker for filtering headers for dbGAP submission.
Generated command line for read filters now correctly prefixes the argument name as --read_filter instead of -read_filter.
Latest WholeGenomePipeline.
Other minor cleanup to utility methods.
-- Not hooked up yet, so the output of VariantEval should be the same as before
-- Implemented a VariantEvalUnitTest that tests the low level strat / eval combinatorics and counting routines
-- Better docs throughout
-- HMS no longer tries to grab and throw all exceptions. Exceptions are just thrown directly now.
-- Proper error handling is handled by functions in HMS, which are used by ShardTraverser and TreeReducer
-- Better printing of stack traces in WalkerTest
-- Unfortunately the result of the multi-threaded test is non-deterministic so run the test 10x times to see if the right expection is always thrown
-- Now prints the stack trace and exception message of the caught exception of the wrong type, if this occurs
* Added parameter -qq to quantize qualities using a recalibration report
* Added options to quantize using the recalibration report quantization levels, new nLevels and no quantization.
* Updated BQSR scripts to make use of the new parameters
-- Now calculates the number of Indels overlapping gold standard sites, as well as the percent of indels overlapping gold standard sites
-- Removed insertion : deletion ratio for 1 bp event, replaced it with 1 + 2 : 3 bp ratio for insertions and deletions separately. This is based on an old email from Mark Daly:
// - Since 1 & 2 bp insertions and 1 & 2 bp deletions are equally likely to cause a
// downstream frameshift, if we make the simplifying assumptions that 3 bp ins
// and 3bp del (adding/subtracting 1 AA in general) are roughly comparably
// selected against, we should see a consistent 1+2 : 3 bp ratio for insertions
// as for deletions, and certainly would expect consistency between in/dels that
// multiple methods find and in/dels that are unique to one method (since deletions
// are more common and the artifacts differ, it is probably worth looking at the totals,
// overlaps and ratios for insertions and deletions separately in the methods
// comparison and in this case don't even need to make the simplifying in = del functional assumption
-- Added a new VEW argument to bind a gold standard track
-- Added two new stratifications: OneBPIndel and TandemRepeat which do exactly what you imagine they do
-- Deleted random unused functions in IndelUtils
Returns true iff VC is an non-complex indel where every allele represents an expansion or
contraction of a series of identical bases in the reference.
The logic of this function is pretty simple. Take all of the non-null alleles in VC. For
each insertion allele of n bases, check if that allele matches the next n reference bases.
For each deletion allele of n bases, check if this matches the reference bases at n - 2 n,
as it must necessarily match the first n bases. If this test returns true for all
alleles you are a tandem repeat, otherwise you are not. Note that in this context n is the
base differences between the ref and alt alleles
* fixed bug where some keys were using the same recal datum objects
* fixed quantization qual calculations when combining multiple reports
* fixed rounding error with empirical quality reported when combining reports
* fixed combine routine in the gatk reports due to the primary keys being out of order
* added auto-recalibration option to BQSR scala script
* reduced the size of the recalibration report by ~15%
* updated md5's
-- Molten now supports variableName and valueName so you don't have to use variable and value if you don't want to.
-- Cleanup code, reorganize a bit more.
-- Fix for broken integrationtests
*** WAY FASTER ***
-- 3x performance for multiple sample analysis with 1000 samples
-- Analyzing 1MB of the ESP call set (3100 samples) takes 40 secs, compared to several minutes in the previous version
-- According to JProfiler all of the runtime is now spent decoding genotypes, which will only get better when we move to BCF2
-- Remove the TableType system, as this was way too complex. No longer possible to embed what were effectively multiple tables in a single Evaluator. You now have to have 1 table per eval
-- Replaced it with @Molten, which allows an evaluator to provide a single Map from variable -> value for analysis. IndelLengthHistogram is now a @Molten data type. GenotypeConcordance is also.
-- No longer allow Evaluators to use private and protected variables at @DataPoints. You get an error if you do.
-- Simplified entire IO system of VE. Refactored into VariantEvalReportWriter.
-- Commented out GenotypePhasingEvaluator, as it uses the retired TableType
-- Stratifications are all fully typed, so it's easy for GATKReports to format them.
-- Removed old VE work around from GATKReportColumn
-- General code cleanup throughout
-- Updated integration tests
-- Added memory and safety optimizations to StratNode and StratificationManager. Fresh, immutable Hashmaps are allocated for final data structures, so they exactly the correct size and cannot be changed by users.
-- Added ability of a stratification to specify incompatible evaluation. The two strats using this are AC and Sample with VariantSummary, as this computes per-sample averages and so combining these results in an O(n^2) memory requirement. Added integration test to cover incompatible strats and evals
-- Renamed and reorganized infrastructure
-- StratificationManager now a Map from List<Object> -> V. All key functions are implemented. Less commonly used TODO
-- Ready for hookup to VE
-- Created a unit tested tree mapping from a List<String> -> integer (StratificationStates). This class is the key infrastructure necessary to create a complete static mapping from all stratification combinations to an offset in a vector of EvalutionContexts for update in map.
-- Minor code cleanup throughout VE (removing unused headers, for example)
- The Integer column type now accepts byte and shorts
- Updated Unit Tests and added a new testParse() test
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
* restructured the hash tables into one class (RecalibrationReport) that has all the functionality for the different tables and key managers
* optmized empirical qual calculation when merging recalibration reports
* centralized the quality score quantization functionalities
* unified the creating/loading of all the key manager/hash table structures.
* added unit tests for the gatherer (disabled because gatk report needs to be sorted for automated testing)
* added integration tests for BQSR and on-the-fly recalibration
-- The previous approach (requiring > 5 copies among all reads) is breaking down in many samples (>1000) just from sequencing errors.
-- This breakdown is producing spurious clustered indels (lots of these!) around real common indels
-- The new approach requires >X% of reads in a sample to carry an indel of any type (no allele matching) to be including in the counting towards 5. This actually makes sense in that if you have enough data we expect most reads to have the indel, but the allele might be wrong because of alignment, etc. If you have very few reads, then the threshold is crossed with any indel containing read, and it's counted.
-- As far as I can tell this is the right thing to do in general. We'll make another call set in ESP and see how it works at scale.
-- Added integration tests to ensure that the system is behaving as I expect on the site I developed the code on from ESP
* restructured BQSR to report recalibrated tables.
* implemented empirical quality calculation to the BQSR stage (instead of on-the-fly recalibration)
* linked quality score quantization to the BQSR stage, outputting a quantization histogram
* included the arguments used in BQSR to the GATK Report
* included all three tables (RG, QUAL and COVARIATES) to the GATK Report with empirical qualities
On-the-fly recalibration with GATK Report
* loads all tables from the GATKReport using existing infrastructure (with minor updates)
* implemented initialiazation of the covariates using BQSR's argument list
* reduced memory usage significantly by loading only the empirical quality and estimated quality reported for each bit set key
* applied quality quantization to the base recalibration
* excluded low quality bases from on-the-fly recalibration for mismatches, insertions or deletions
-- This behavior, which isn't obviously valuable at all, continued to grab and rethrow exceptions in the HMS that, if run without NT, would show up as more meaningful errors. Now HMS simply checks whether the throwable it received on error was a RuntimeException. If so, it is stored and rethrow without wrapping later. If it isn't, only in this case is the exception wrapped in a ReviewedStingException.
-- Added a QC walker ErrorThrowingWalker that will throw a UserException, ReviewedStingException, and NullPointerException from map as specified on the command line
-- Added IT that ensures that all three types are thrown properly (i.e., you catch a NullPointerException when you ask for one to be thrown) with and without threading enabled.
-- I believe this will finally put to rest all of these annoying HMS captures.
-- Now you always get SNP and indel metrics with VariantEval!
-- Includes Number of SNPs, Number of singleton SNPs, Number of Indels, Number of singleton Indels, Percent of indel sites that are multi-allelic, SNP to indel ratio, Singleton SNP to indel ratio, Indel novelty rate, 1 to 2 bp indel ratio, 1 to 3 bp indel ratio, 2 to 3 bp indel ratio, 1 and 2 to 3 bp indel ratio, Frameshift percent, Insertion to deletion ratio, Insertion to deletion ratio for 1 bp events, Number of indels in protein-coding regions labeled as frameshift, Number of indels in protein-coding regions not labeled as frameshift, Het to hom ratio for SNPs, Het to hom ratio for indels, a Histogram of indel lengths, Number of large (>10 bp) deletions, Number of large (>10 bp) insertions, Ratio of large (>10 bp) insertions to deletions
-- Updated VE integration tests as appropriate
* fixed BadCigarFilter to filter out reads starting/ending in deletion and that have adjacent I/D events.
* added Unit tests for BadCigarFilter
* updated all exceptions in LocusIteratorByState to tell the user that he can instead run with -rf BadCigar
* added the BadCigar filter to ReduceReads and RealignTargetCreator (if your walker blows up with these malformed reads, you may want to add it too)
- Updated the documentation on the code
- Made the table.write() method private and updated necessary files.
- Added a constructor to GATKReport that takes GATKReportTables
- Optimized my code
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
This is important for quick turnaround in the analysis cycle of the new covariates. Also added a dummy unit test that doesn't really test anything (disabled), but helps in debugging.
Infrastructure:
* Added static interface to all different clipping algorithms of low quality tail clipping
* Added reverse direction pileup element event lookup (indels) to the PileupElement and LocusIteratorByState
* Complete refactor of the KeyManager. Much cleaner implementation that handles keys with no optional covariates (necessary for on-the-fly recalibration)
* EventType is now an independent enum with added capabilities. All functionality is now centralized.
BQSR and RecalibrateBases:
* On-the-fly recalibration is now generic and uses the same bit set structure as BQSR for a reduced memory footprint
* Refactored the object creation to take advantage of the compact key structure
* Replaced nested hash maps with single hash maps indexed by bitsets
* Eliminated low quality tails from the context covariate (using ReadClipper's write N's algorithm).
* Excluded contexts with N's from the output file.
* Fixed cycle covariate for discrete platforms (need to check flow cycle platforms now!)
* Redfined error for indels to look at the previous base in negative strand reads (using new PE functionality)
* Added the covariate ID (for optional covariates) to the output for disambiguation purposes
* Refactored CovariateKeySet -- eventType functionality is now handled by the EventType enum.
* Reduced memory usage of the BQSR script to 4
Tests:
* Refactored BQSRKeyManagerUnitTest to handle the new implementation of the key manager
* Added tests for keys without optional covariates
* Added tests for on-the-fly recalibration (but more tests are necessary)
Infrastructure:
* Generic BitSet implementation with any precision (up to long)
* Two's complement implementation of the bit set handles negative numbers (cycle covariate)
* Memoized implementation of the BitSet utils for better performance.
* All exponents are now calculated with bit shifts, fixing numerical precision issues with the double Math.pow.
* Replace log/sqrt with bitwise logic to get rid of numerical issues
BQSR:
* All covariates output BitSets and have the functionality to decode them back into Object values.
* Covariates are responsible for determining the size of the key they will use (number of bits).
* Generalized KeyManager implementation combines any arbitrary number of covariates into one bitset key with event type
* No more NestedHashMaps. Single key system now fits in one hash to reduce hash table objects overhead
Tests:
* Unit tests added to every method of BitSetUtils
* Unit tests added to the generalized key system infrastructure of BQSRv2 (KeyManager)
* Unit tests added to the cycle and context covariates (will add unit tests to all covariates)
-- TODO for ryan -- there are bugs in ActivityProfile code that I cannot fix right now :-(
-- UnitTesting framework for ActivityProfile -- needs to be expanded
-- Minor helper functions for ActiveRegion to help with unit tests
-- This report details which intervals are coming in and how many reads they contain
-- Added integration test to verify that the intervals aren't changing, before heading into the ART refactor
GATKReport format changes:
- All non-data header lines are preceeded with a single pound ( #:)
- Every report now has a report header containing the version number and number of tables
- Every table has two lines of table header: The first explains the size of the table and the data types of each column, the second contains the table name and description.
- This new format will allow reports in the future to be gatherable.
- Changed the header format to include an end-of-line string ":;"
Added features:
- Simplified GATK Reports:
The constructor for a simplified GATK Report. Simplified GATK report are designed for reports that do not need the advanced functionality of a full GATK Report.
A simple GATK Report consists of:
- A single table
- No primary key ( it is hidden )
Optional:
- Only untyped columns. As long as the data is an Object, it will be accepted.
- Default column values being empty strings.
Limitations:
- A simple GATK report cannot contain multiple tables.
- It cannot contain typed columns, which prevents arithmetic gathering.
- Added a constructor to generate simplified GATK reports.
- Added a method to easily add data to simple GATK reports.
- Upgraded the input parser take advantage of the new file format (v1).
- Added the GATKReportGatherer, more usability cmoing in next versionof GATK Report. Curently, it can only add rows from one table to another. Added private methods in GATKReport to combine Tables and Reports, It is very conservative and will only gather if the table columns, as well as everything else matches. At the column level, it uses the (redundant) row ids to add new rows. It will throw an exception if it is overwriting data.
- Made some GATKReport methods public, and added more setters and getters.
- Added method that compares formats of two GATKReports, and added an equals method to verify all data inside.
- The gsalib for R now supports reading GATKReport v1 files in addition to legacy formats (v0.*)
- Added a GATKReportDataType enum to give column a certain data type. This must be specified when making a gatherable report. This enum contains several methods including a reverse lookup map.
- Added a data type field in GATKColumn, when a type is not specified, the unknown type is used. Unknown types should not be gathered.
Test changes:
- Updated Unit Tests for GATK Report v1. Added a test for the gatherer. Left one test disabled while we transition from v0 to v1.
- Updated the MD5 hashes in integration tests throughout the GATK.
Other changes:
- Added the gatherer functions to CoverageByRG
- Also added the scatterCount parameter in the Interval Coverage script
- Dropped support for reading in legacy GATKReport formats ( v0.*)
- Updated VariantEvalWalker to work with GATK Report v1, added a format String to all applicable DataPoints.
- Rewrote the read file method for GATK report files.
- Optimized the equals methods within GATKReport. The protected functions should only be called by the GATKReport methods.
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
-- Refactored some duplicated code (FYI, code duplication = root of all evil) into shared functions
-- Added long-missing integrationtests
-- CHRIS/RYAN -- it would be very good to add an integration test covering external VCF files as I believe we rely on this functionality and it's not tested at all
GATKBAMIndex would allow an extremely confusing BufferUnderflowException to be
thrown when a BAM index file was truncated or corrupt. Now, a UserException is
thrown in this situation instructing the user to re-index the BAM.
Added a unit test for this case as well.
-- A cleaner table output (molten). For those interested in seeing how this can be done with GATKReports look here for a nice clean example
-- Integration tests
-- Minor improvements to GATKReportTable with methods to getPrimaryKeys
-- We weren't properly handling the case where a site had both a SNP and indel in both eval and comp. These would naturally pair off as SNP x SNP and INDEL x INDEL in eval, but we'd still invoke update2 with (null, SNP) and (null, INDEL) resulting most conspicously as incorrect false negatives in the validation report.
-- Updating misc. integrationtests, as the counting of comps (in particular for dbSNP) was inflated because of this effect.
Several of the unit tests for the new key authorization feature require
read access to the GATK master private key file. Since this file is only
readable by members of the group gsagit, this makes it hard for people
outside the group to run the test suite.
Now, we skip tests that require the master private key if the private
key exists (since not existing would be a true error) but is not readable
by the user running the test suite
Bamboo, of course, will always be able to run these tests.
-Running the GATK with the -et NO_ET or -et STDOUT options now
requires a key issued by us. Our reasons for doing this, and the
procedure for our users to request keys, are documented here:
http://www.broadinstitute.org/gsa/wiki/index.php/Phone_home
-A GATK user key is an email address plus a cryptographic signature
signed using our private key, all wrapped in a GZIP container.
User keys are validated using the public key we now distribute with
the GATK. Our private key is kept in a secure location.
-Keys are cryptographically secure in that valid keys definitely
came from us and keys cannot be fabricated, however keys are not
"copy-protected" in any way.
-Includes private, standalone utilities to create a new GATK user key
(GenerateGATKUserKey) and to create a new master public/private key
pair (GenerateKeyPair). Usage of these tools will be documented on
the internal wiki shortly.
-Comprehensive unit/integration tests, including tests to ensure the
continued integrity of the GATK master public/private key pair.
-Generation of new user keys and the new unit/integration tests both
require access to the GATK private key, which can only be read by
members of the group "gsagit".
-- Includes paired end status (T/F)
-- Includes count of reads used in calculation
-- Includes simple read type (2x76 for example)
-- Better handling of insert size, read length when there's no data, or the data isn't paired end by emitting NA not 0
-- ReadGroupProperties: Emits a GATKReport containing read group, sample, library, platform, center, median insert size and median read length for each read group in every BAM file.
-- Median tool that collects up to a given maximum number of elements and returns the median of the elements.
-- Unit and integration tests for everything.
-- Making name of TestProvider protected so subclasses and override name more easily
* Turns DNA sequences (for context covariates) into bit sets for maximum compression
* Allows variable context size representation guaranteeing uniqueness.
* Works with long precision, so it is limited to a context size of 31 bases (can be extended with BigNumber precision if necessary).
* Unit Tests added
-- DoC now by default ignores bases with reference Ns, so these are not included in the coverage calculations at any stage.
-- Added option --includeRefNSites that will include them in the calculation
-- Added integration tests that ensures the per base tables (and so all subsequent calculations) work with and without reference N bases included
-- Reorganized command line options, tagging advanced options with @Advanced
When aggregating raw BAM file spans into shards, the IntervalSharder tries to combine
file spans when it can. Unfortunately, the method that combines two BAM file
spans was seriously flawed, and would produce a truncated union if the file spans
overlapped in certain ways. This could cause entire regions of the BAM file containing
reads within the requested intervals to be dropped.
Modified GATKBAMFileSpan.union() to correct this problem, and added unit tests
to verify that the correct union is produced regardless of how the file spans
happen to overlap.
Thanks to Khalid, who did at least as much work on this bug as I did.
* added support to base before deletion in the pileup
* refactored covariates to operate on mismatches, insertions and deletions at the same time
* all code is in private so original BQSR is still working as usual in public
* outputs a molten CSV with mismatches, insertions and deletions, time to play!
* barely tested, passes my very simple tests... haven't tested edge cases.
premature push from my part. Roger is still working on the new format and we need to update the other tools to operate correctly with the new GATKReport.
This reverts commit aea0de314220810c2666055dc75f04f9010436ad.
- Added the GATKReportGatherer
- Added private methods in GATKReport to combine Tables and Reports
- It is very conservative and it will only gather if the table columns, match.
- At the column level it uses the (redundant) row ids to add new rows. It will throw an exception if it is overwriting data.
Added the gatherer functions to CoverageByRG
Also added the scatterCount parameter in the Interval Coverage script
Made some more GATKReport methods public
The UnitTest included shows that the merging methods work
Added a getter for the PrimaryKeyName
Fixed bugs that prevented the gatherer form working
Working GATKReportGatherer
Has only the functional to addLines
The input file parser assumes that the first column is the primary key
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
* new unit tests for the alignment shift properties of reduce reads
* moved unit tests from ReadUtils that were actually testing GATKSAMRecord, not any of the ReadUtils to it.
* cleaned up ReadUtilsUnitTest
Eric reported this bug due to the reduced reads failing with an index out of bounds on what we thought was a deletion, but turned out to be a read starting with insertion.
* Refactored PileupElement to distinguish clearly between deletions and read starting with insertion
* Modified ExtendedEventPileup to correctly distinguish elements with deletion when creating new pileups
* Refactored most of the lazyLoadNextAlignment() function of the LocusIteratorByState for clarity and to create clear separation between what is a pileup with a deletion and what's not one. Got rid of many useless if statements.
* Changed the way LocusIteratorByState creates extended event pileups to differentiate between insertions in the beginning of the read and deletions.
* Every deletion now has an offset (start of the event)
* Fixed bug when LocusITeratorByState found a read starting with insertion that happened to be a reduced read.
* Separated the definitions of deletion/insertion (in the beginning of the read) in all UG annotations (and the annotator engine).
* Pileup depth of coverage for a deleted base will now return the average coverage around the deletion.
* Indel ReadPositionRankSum test now uses the deletion true offset from the read, changed all appropriate md5's
* The extra pileup elements now properly read by the Indel mode of the UG made any subsequent call have a different random number and therefore all RankSum tests have slightly different values (in the 10^-3 range). Updated all appropriate md5s after extremely careful inspection -- Thanks Ryan!
phew!
-- Missing BAMs were appearing as StingExceptions
-- Missing VCFs were showing up as CommandLineErrors, but it's clearer for them to be CouldNotReadInputFile exceptions
-- Added integration tests to ensure missing BAMs, VCFs, and -L files are properly thrown as CouldNotReadInputFile exceptions
-- Added path to standard b37 BAM to BaseTest
-- Cleaned up code in SAMDataSource, removing my parallel loading code as this just didn't prove to be useful.
This is somewhat of an arbitrary decision, and is negotiable. I could see treating
GT:PL ./.:.
differently from
GT:PL .:0,3,6
but am not sure the worth of doing so.
* using the filter() instead of map() makes for a cleaner walker.
* renaming the unit tests to make more sense with the other unit and integration tests
* if the adaptor boundary is more than MAXIMUM_ADAPTOR_SIZE bases away from the read, then let's not clip anything and consider the fragment to be undetermined for this read pair.
* updated md5's accordingly
-- Call sets with indels > 50 bp in length are tagged as CNVs in the tag (following the 1000 Genomes convention) and were unconditionally checking whether the CNV is already known, by looking at the known cnvs file, which is optional. Fixed. Has the annoying side effect that indels > 50bp in size are not counted as indels, and so are substrated from both the novel and known counts for indels. C'est la vie
-- Added integration test to check for this case, using Mauricio's most recent VCF file for NA12878 which has many large indels. Using this more recent and representative file probably a good idea for more future tests in VE and other tools. File is NA12878.HiSeq.WGS.b37_decoy.indel.recalibrated.vcf in Validation_Data
Some tests in this class were intermittently not being executed due
to being randomly scheduled before tests whose results they depend on.
Now the serial dependencies are enforced to avoid problematic orderings.
* Knuth-shuffle is a simple, yet effective array permutator (hope this is good english).
* added a simple randomSubset that returns a random subset without repeats of any given array with the same probability for every permutation.
* added unit tests to both functions
* Modified cleanCigarShift to allow insertions in the beginning and end of the read
* Allowed cigars starting/ending in insertions in the systematic ReadClipper tests
* Updated all ReadClipper unit tests
* ReduceReads does not hard clip leading insertions by default anymore
* SlidingWindow adjusts start location if read starts with insertion
* SlidingWindow creates an empty element with insertions to the right
* Fixed all potential divide by zero with totalCount() (from BaseCounts)
* Updated all Integration tests
* Added new integration test for multiple interval reducing
These functions are methods of the read, and supplement getAlignmentStart() and getUnclippedStart() by calculating the unclipped start counting only soft clips.
* Removed from ReadUtils
* Added to GATKSAMRecord
* Changed name to getSoftStart() and getSoftEnd
* Updated third party code accordingly.
The algorithm wasn't accounting for the case where the read is the reverse strand and the insert size is negative.
* Fixed and rewrote for more clarity (with Ryan, Mark and Eric).
* Restructured the code to handle GATKSAMRecords only
* Cleaned up the other structures and functions around it to minimize clutter and potential for error.
* Added unit tests for all 4 cases of adaptor boundaries.
* New ClippingOp REVERT_SOFTCLIPPED_BASES turns soft clipped bases into matches.
* Added functionality to clipping op to revert all soft clip bases in a read into matches
* Added revertSoftClipBases function to the ReadClipper for public use
* Wrote systematic unit tests
Creating a single temporary directory per ant test run instead of a putting temp files across all runs in the same directory.
Updated various tests for above items and other small fixes.
fixed issue where a read starting with an insertion followed by a deletion would break, clipper can now safely clip the insertion and the deletion if that's the case.
note: test is turned off until contract changes to allow hanging insertions (left/right).
* fixed edge case when requested to hard clip beginning of a read that had hanging soft clipped bases on the left tail.
* fixed edge case when requested to hard clip end of a read that had hanging soft clipped bases on the right tail.
* fixed AlignmentStart of a clipped read that results in only hard clips and soft clips
note: added tests to all these beautiful cases...
* expanded the systematic cigar string space test framework Roger wrote to all tests
* moved utility functions into Utils and ReadUtils
* cleaned up unused classes
caught a bug in the hard clipper where it does not account for hard clipping softclipped bases in the resulting cigar string, if there is already a hard clipped base immediately after it.
* updated unit test for hardClipSoftClippedBases with corresponding test-case.
bug: When performing multiple hard clip operations in a read that has indels, if the N+1 hardclip requests to clip inside an indel that has been removed by one of the (1..N) previous hardclips, the hard clipper would go out of bounds.
fix: dynamically adjust the boundaries according to the new hardclipped read length. (this maintains the current contract that hardclipping will never return a read starting or ending in indels).
-- Now properly handles the case where a sample isn't present (no longer adds a null to the genotypes list)
-- Fix for logic failure where if the number of requested samples equals the number of known genotypes then all of the records were returned, which isn't correct when there are missing samples.
-- Unit tests added to handle these cases
Tests are more rigorous and includes many more test cases.
We can tests custom cigars and the generated cigars.
*Still needs debugging because code is not working.
Created test classes to be used across several tests.
Some cases are still commented out.
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
Insertions are a problem so cigar cases with "I" are commented out.
The test works with multiple deletions and matches.
This is still not a complete test. A lot of cigar test cases are commented out.
Added insertions to ReadClipperUnitTest
ReadClipper now tests for all indels.
Signed-off-by: Mauricio Carneiro <carneiro@broadinstitute.org>
PreQC parses file with spaces in sample names by using tabs only.
PostQC allows passing the file names for the evals so that flanks can be evaled.
BaseTest's network temp dir now adds the user name to the path so files aren't created in the root.
HybridSelectionPipeline:
- Updated to latest versions of reference data.
- Refactored Picard parsing code replacing YAML.
-- VariantSummary now includes novelty of CNVs by reciprocal overlap detection using the standard variant eval -knownCNVs argument
-- Genericizes loading for intervals into interval tree by chromosome
-- GenomeLoc methods for reciprocal overlap detection, with unit tests
-- Performance optimizations
-- Tables now are cleanly formatted (floats are %.2f printed)
-- VariantSummary is a standard report now
-- Removed CompEvalGenotypes (it didn't do anything)
-- Deleted unused classes in GenotypeConcordance
-- Updates integration tests as appropriate
-- Updating MD5s for UG to reflect that what was previously called ./.:.:10:0,0,0 is now just ./. Eric will fix long-standing bug in QD observed from this change
-- VFW MD5s restored to their old correct values. There was a bug in my implementation to caused the genotypes to not be parsed from the lazy output even through the header was incorrect.
This syntax predates the ability to have multiple -L arguments, is
inconsistent with the syntax of all other GATK arguments, requires
quoting to avoid interpretation by the shell, and was causing
problems in Queue.
A UserException is now thrown if someone tries to use this syntax.
-- Now you provide a LazyParsing object
-- LazyGenotypesContext now knows nothing about the VCF parser itself. The parser holds all of the necessary data to parse the VCF genotypes when necessarily, and the LGC only has a pointer to this object
-- Using new interface added LazyGenotypesContext to unit tests with a simple lazy version
-- Deleted VCFParser interface, as it was no longer necessary
-- With our GenotypesContext class we can naturally create a LazyGenotypesContext subclass that does the on-demand loading.
-- This new class was replaced all of the old, complex functionality
-- Better still, there were many cases were the genotypes were being loaded unnecessarily, resulting in efficiency. This was detected because some of the integration tests changed as the genotypes were no longer being parsing unnecessarily
-- Misc. bug fixes throughout the system
-- Bug fixes for PhaseByTransmission with new GenotypesContext
-- We should no longer have md5s changing because of hashmaps changing their sort order on us
-- Added GenotypeLikelihoodsUnitTests
-- Refactored ExactAFCaclculation to put the PL -> QUAL calculation in the GenotypeLikelihoods class to avoid the code copy.
-- New approach to making VariantContexts modeled on StringBuilder
-- No more modify routines -- use VariantContextBuilder
-- Renamed isPolymorphic to isPolymorphicInSamples. Same for mono
-- getChromosomeCount -> getCalledChrCount
-- Walkers changed to use new VariantContext. Some deprecated new VariantContext calls remain
-- VCFCodec now uses optimized cached information to create GenotypesContext.
-- Major change to how chromosomeCounts is computed. Now NO_CALL alleles are always excluded. So ChromosomeCounts(A/.) is 1, the previous result would have been 2.
-- Naming changes for getSamplesNameInOrder()
-- Compares performance across a bunch of common operations with GATK 1.3 version of VariantContext and GATK 1.4
-- 1.3 VC and associated utilities copied wholesale into test directory under v13
-Modified the SnpEff parser to work with the SnpEff 2.0.4 VCF output format
-Assigning functional classes and effect impacts now handled directly
by SnpEff rather than the GATK
-Removed support for SnpEff 2.0.2, as we no longer trust the output of that
version since it doesn't exclude effects associated with certain nonsensical
transcripts. These effects are excluded as of 2.0.4.
-Updated unit and integration tests
This support is based on a *release-candidate* of SnpEff 2.0.4, and so is subject
to change between now and the next GATK release.
compressed the representation of the reduce reads counts by offset results in 17% average compression in final BAM file size.
Example compression -->
from : 10, 10, 11, 11, 12, 12, 12, 11, 10
to: 10, 0, 1, 1,2, 2, 2, 1, 0
-- I have no idea why I named this InferredGeneticContext, a totally meaningless term
-- Renamed to CommonInfo.
-- Made package protected, as no one should use this outside of VariantContext and Genotype
-- UGEngine was using IGC constant, but it's now using the public one in VariantContext.
-- Enables further sophisticated optimizations, as this class can be smarter about storing the data and will directly support operations like subset to samples
-- All instances in the gatk that used Map<String, Genotype> now use GenotypeMap type.
-- Amazingly, there were many places where HashMap<String, Genotype> is used, so that the order of the genotypes is technically undefined and could be dangerous. Now everything uses GenotypeMap with a specific ordering of samples (by name)
-- Integrationtests updated and all pass
* Generalized the concept of a synthetic read to cread both running consensus and a synthetic reads of filtered data.
* Synthetic reads can now have deletions (but not insertions)
* New reduced read tag for filtered data synthetic reads *(RF)*
* Sliding window header now keeps information of consensus and filtered data
* Synthetic reads are created simultaneously, new functionality is controlled internally by addToSyntheticReads
The GATK engine will now provide a GATKSAMRecord to all tools which incorporates the functionality used by the GATK to the bam file (ReadGroups, Reduced Reads, ...).
* No tools should create SAMRecord anymore, use GATKSAMRecord instead *
-- scatterLocusIntervals master utility
-- Moved around some general functionality from GenomeLocSortedSet to GenomeLoc
-- Util function for reversing a list (List<T> -> List<T>, unlike Collections version)
-- DoC is PartitionType.INTERVAL
-- Significant unit tests on new functionality (all passing)
-- Ready for real-world testing, as soon as I can get LocusScatterFunction.scala to actually work
-- Supports ReadBackedPileup -> FragmentCollection as before
-- Added support for List<SAMRecord> -> FragmentCollection for Ryan's haplotype caller
-- General cleanup, renaming, move to separate package, more extensive unit tests, etc.
-- Added toFragment() function to ReadBackedPileup interface
Moved gsalib and queueJobReport.R to embeddable namespaced locations.
Updated packager dependencies/dir to add an @includes which filters the embedded fileset.
RScriptExecutor can now JIT compiles the gsalib.
RScriptExecutor uses ProcessController and sends the Rscript output to java's stdout when run under -l DEBUG.
Refactored ProcessController and IOUtils from Queue to Sting Utils.
Added more unit tests to ProcessController along with a utility class to hard stop OutputStreams at a specified byte count.
Replaced uses of some IOUtils with Apache Commons IO.
ShellJobRunner refactored to use direct ProcessController and now kills jobs on shutdown.
Better QGraph responsiveness on shutdown by using Object.wait() instead of Thread.sleep().
-- removed intermiate functions. Now only original version and best optimized new version remain
-- Moved general artificial read backed pileup creation code into ArtificialSamUtils
-- Uses mayOverlapRoutine in ReadUtils
-- Attempts to be smart when doing overlap calculation, to avoid unnecessary allocations
-- PileupElement now comparable (sorts on offset than on start)
-- Caliper microbenchmark to assess performance
-- Creates all combinatinos of overlapping and non-overlapping read pair pileups in all orientations and first/second pairings to validate fragment detection.
We can't have a public test that depends on both public and private
code/data -- the new release system needs to do public-only tests,
and will catch this sort of thing.
The public integration test VariantContextIntegrationTest was dependent on the
private walker TestVariantContextWalker. Moved this walker to public/java/test
(NOT public/java/src, since this walker is only used by the test suite) to avoid
errors during public-only tests.
-- MD5 db had spelling error; fixed
-- Bug in AlignmentUtils resulted in some bases not being color space corrected. The integration test caught the change, and it's clear that the new version is correct, as the prev. version was not considering the last the N qualities for reads with a ND operation.
This allows the annotation classes to perform any necessary initialization/validation.
For example, it allows the SnpEff annotator to (among other things) validate its rod binding.
This will prevent a NullPointerException when SnpEff annotation is requested but no rod binding
is present.
Added an integration test to cover this case so that it doesn't break again.
-- Changes associated code throughout the codebase
-- Updated necessary (but minimal) UnitTests to reflect new behavior
-- Much better makealleles() function in VC.java that enforces a lot of key constraints in VC
classloading of bcel*.jar/ant-apache-bcel*.jar. Switching instead to manually
specifying a minimal set of packages/classes to include in the vcf.jar via
build.xml, and adding a unit test which creates a limited classloader
only aware of vcf.jar and tribble.jar and tries to use it to load the core
classes in the vcf jar.
Hopefully third time's the charm.
-- the underlying data structure is still present, but until I decide what to do for the extensible system I've completely disabled the subsystem
-- Added code to merge Samples, so that a mostly full record can be merged with a consistent empty record. If the two records are inconsistent, an error is thrown
-- addSample() in Sample.class now invokes mergeSample() when appropriate
-- Validation types are now only STRICT or SILENT
-- Validation code implemented in SampleDBBuilder
-- Extensive unit tests for SampleDBBuilder
-- Passes significiant unit tests
-- Implicit sample creation for mom / dad when you create single samples
-- Continuing cleanup of Sample and SampleDataSource
Khalid Shakir
Eric Banks
Guillermo del Angel
Laurent Francioli
Mark DePristo
Mauricio Carneiro
Ryan Poplin
Roger Zurawicki
Menachem Fromer
David Roazen
Christopher Hartl
Matt Hanna
Laurent Francioli