This test passes when run individually, as part of the commit tests, or as
part of the package tests. However, when running the unit tests in isolation
it causes maven/surefire to throw a NoSuchElementException.
This is clearly a maven/surefire bug or configuration issue. I will re-enable
this test on a branch as Khalid and I try to work through it.
-Hide AWS downloader credentials in a private properties file
-Remove references to private ActiveRegion walker
Allows phone home functionality to be tested at release time
when we are running tests on the release jar.
1. Enable on-the-fly indexing for vcf.gz.
2. Handle on-the-fly indexing where file to be indexed is not a regular file, thus index should not be created.
3. Add method setProgressLogger to all SAMFileWriter implementations.
4. Revved picard to 1.109.1722
5. IndelRealigner md5s change because the MC tag is added to records now.
Fixed up and signed off by ebanks.
Package tests now hard coding just the gatk-framework tests jar, to include ONLY BaseTest, until the exclusions may be debugged.
Removing cofoja's annotation service from the package jars, to allow javac -cp <package>.jar.
Currently the best haplotypes are those that accumulate the largest ABSOLUTE edge *multiplicity* sum across their path in the assembly graph.
The edge *mulitplicity* is equal to the number of reads that expand through that edge, i.e. have a kmer that uniquely map to some vertex up-stream from the edge and the following base calls extend across that edge to vertices downstream from it.
Despite that it is obvious that higher multiplicties correlated with haplotype probability this criterion fails short in some regards of which the most relevant is:
As it is evaluated in condensed seq-graph (as supposed to uncompressed read-threading-graphs) it is bias to haplotypes that have more short-sequence vetices
( -> ATGC -> CA -> has worse score than -> A -> T -> G -> C -> C -> A ->). This is partly result of how we modify the edge multiplicities when we merge vertices from a linear chain.
This pull-request addresses the problem by changing to a new scoring schema based in likelihood estimates:
Each haplotype's likelihood can be calculated as the multiplication of the likelihood of "taking" its edges in the assembly graph. The likelihood of "taking" an edge in the assembly
graph is calculated as its multiplicity divide by the sum of multiplicity of edges that share the same source vertex.
This pull-request addresses the following stories:
https://www.pivotaltracker.com/story/show/66691418https://www.pivotaltracker.com/story/show/64319760
Change Summary:
1. Change to the new scoring schema.
2. Added a graph DOT printing code to KBestHaplotypeFinder in order to diagnose scoring.
3. Graph transformation have been modified in order to generate no 0-multiplicity edges. (Nevertheless the schema above should work with 0 edges assuming that they are in fact 0.5)
The maven shade plugin was eliminating a necessary class (IgnoreCookiesSpec)
when packaging the GATK/Queue. Work around this by telling maven to
always package all of commons-httpclient.
Enable it with the new --useIUPAC argument.
Added both unit and integration tests for the new functionality - and fixed up the
exising tests once I was in there.
-These tests are really integration tests for Queue rather than generalized
pipeline tests, so it makes sense to call them QueueTests.
-Rename test classes and maven build targets, and update shell scripts
to reflect new naming.
This module was causing failures during the release
packaging tests. After discussing with Khalid, we've
decided to disable it for now until a fix can be
developed.
C++ code has PAPI calls for reading hardware counters
Followed Khalid's suggestion for packing libVectorLoglessCaching into
the jar file with Maven
Native library part of git repo
1. Renamed directory structure from public/c++/VectorPairHMM to
public/VectorPairHMM/src/main/c++ as per Khalid's suggestion
2. Use java.home in public/VectorPairHMM/pom.xml to pass environment
variable JRE_HOME to the make process. This is needed because the
Makefile needs to compile JNI code with the flag -I<JRE_HOME>/../include (among
others). Assuming that the Maven build process uses a JDK (and not just
a JRE), the variable java.home points to the JRE inside maven.
3. Dropped all pretense at cross-platform compatibility. Removed Mac
profile from pom.xml for VectorPairHMM
Moved JNI_README
1. Added the catch UnsatisfiedLinkError exception in
PairHMMLikelihoodCalculationEngine.java to fall back to LOGLESS_CACHING
in case the native library could not be loaded. Made
VECTOR_LOGLESS_CACHING as the default implementation.
2. Updated the README with Mauricio's comments
3. baseline.cc is used within the library - if the machine supports
neither AVX nor SSE4.1, the native library falls back to un-vectorized
C++ in baseline.cc.
4. pairhmm-1-base.cc: This is not part of the library, but is being
heavily used for debugging/profiling. Can I request that we keep it
there for now? In the next release, we can delete it from the
repository.
5. I agree with Mauricio about the ifdefs. I am sure you already know,
but just to reassure you the debug code is not compiled into the library
(because of the ifdefs) and will not affect performance.
1. Changed logger.info to logger.warn in PairHMMLikelihoodCalculationEngine.java
2. Committing the right set of files after rebase
Added public license text to all C++ files
Added license to Makefile
Add package info to Sandbox.java
Conflicts:
protected/gatk-protected/src/main/java/org/broadinstitute/sting/gatk/walkers/haplotypecaller/HaplotypeCaller.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/gatk/walkers/haplotypecaller/PairHMMLikelihoodCalculationEngine.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/utils/pairhmm/DebugJNILoglessPairHMM.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/utils/pairhmm/JNILoglessPairHMM.java
protected/gatk-protected/src/main/java/org/broadinstitute/sting/utils/pairhmm/VectorLoglessPairHMM.java
public/VectorPairHMM/src/main/c++/.gitignore
public/VectorPairHMM/src/main/c++/LoadTimeInitializer.cc
public/VectorPairHMM/src/main/c++/LoadTimeInitializer.h
public/VectorPairHMM/src/main/c++/Makefile
public/VectorPairHMM/src/main/c++/Sandbox.cc
public/VectorPairHMM/src/main/c++/Sandbox.h
public/VectorPairHMM/src/main/c++/Sandbox.java
public/VectorPairHMM/src/main/c++/Sandbox_JNIHaplotypeDataHolderClass.h
public/VectorPairHMM/src/main/c++/Sandbox_JNIReadDataHolderClass.h
public/VectorPairHMM/src/main/c++/baseline.cc
public/VectorPairHMM/src/main/c++/define-double.h
public/VectorPairHMM/src/main/c++/define-float.h
public/VectorPairHMM/src/main/c++/define-sse-double.h
public/VectorPairHMM/src/main/c++/define-sse-float.h
public/VectorPairHMM/src/main/c++/headers.h
public/VectorPairHMM/src/main/c++/jnidebug.h
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_DebugJNILoglessPairHMM.cc
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_DebugJNILoglessPairHMM.h
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_VectorLoglessPairHMM.cc
public/VectorPairHMM/src/main/c++/org_broadinstitute_sting_utils_pairhmm_VectorLoglessPairHMM.h
public/VectorPairHMM/src/main/c++/pairhmm-template-kernel.cc
public/VectorPairHMM/src/main/c++/pairhmm-template-main.cc
public/VectorPairHMM/src/main/c++/run.sh
public/VectorPairHMM/src/main/c++/shift_template.c
public/VectorPairHMM/src/main/c++/utils.cc
public/VectorPairHMM/src/main/c++/utils.h
public/VectorPairHMM/src/main/c++/vector_function_prototypes.h
-- throws UserException; added tests in PosteriorLikelihoodsUtilsUnitTests
Add error handling to CalculateGenotypePosteriors for cases where MLEAC>AN; add tests in PosteriorLikelihoodsUtilsUnitTests
Add unit tests to confirm that CalculateGenotypePosteriors has the ability to switch genotypes for four cases
Changes:
1. Addressed review comments on new K-best haplotype assembly graph finder.
2. Generalize KBestHaplotypeFinder to deal with multiple source and sink vertices.
3. Updated test to use KBestHaplotypeFinder instead of KBestPaths
4. Retired KBestPaths to the archive.
5. Small improvements to the code and documentation.
Story:
https://www.pivotaltracker.com/story/show/66238286
Changes:
1. Created a new k-best haplotype search implementation in class KBestHaplotypeFinder.
2. Changed HC code to use the new implementation.
This seems to fix the original problem without causing significant changes in outputs using some empirical data test cases
3. Moved haplotype's cigar calculation code from Path to CigarUtils; need that in order to gain independence from Path in some parts of the code.
In any case that seems like a more natural location for that functionality.
The GATK now fails with a user error if you try to run with a reduced bam.
(I added a unit test for that; everything else here is just the removal of all traces of RR)
PairHMMLikelihoodCalculationEngine.java to fall back to LOGLESS_CACHING
in case the native library could not be loaded. Made
VECTOR_LOGLESS_CACHING as the default implementation.
2. Updated the README with Mauricio's comments
3. baseline.cc is used within the library - if the machine supports
neither AVX nor SSE4.1, the native library falls back to un-vectorized
C++ in baseline.cc.
4. pairhmm-1-base.cc: This is not part of the library, but is being
heavily used for debugging/profiling. Can I request that we keep it
there for now? In the next release, we can delete it from the
repository.
5. I agree with Mauricio about the ifdefs. I am sure you already know,
but just to reassure you the debug code is not compiled into the library
(because of the ifdefs) and will not affect performance.
-- Keep a list of processed files in ArgumentTypeDescriptor.getRodBindingsCollection
-- Throw user exception if a file name duplicates one that was previously parsed
-- Throw user exception if the ROD list is empty
-- Added two unit tests to RodBindingCollectionUnitTest
public/VectorPairHMM/src/main/c++ as per Khalid's suggestion
2. Use java.home in public/VectorPairHMM/pom.xml to pass environment
variable JRE_HOME to the make process. This is needed because the
Makefile needs to compile JNI code with the flag -I<JRE_HOME>/../include (among
others). Assuming that the Maven build process uses a JDK (and not just
a JRE), the variable java.home points to the JRE inside maven.
3. Dropped all pretense at cross-platform compatibility. Removed Mac
profile from pom.xml for VectorPairHMM
Re-added import java.io.File for BamGatherFunction.
Other cleanup to resolve scala syntax warnings from intellij.
Moved Example UG script to from protected to public.
- This change means that BamGatherFunction will now have an @Output field for the BAM index, which will allow the bai to be deleted for intermediate functions
Signed-off-by: Khalid Shakir <kshakir@broadinstitute.org>
Bug uncovered by some untrimmed alleles in the single sample pipeline output.
Notice however does not fix the untrimmed alleles in general.
Story:
https://www.pivotaltracker.com/story/show/65481104
Changes:
1. Fixed the bug itself.
2. Fixed non-working tests (sliently skipped due to exception in dataProvider).
Note that this tool is still a work in progress and very experimental, so isn't 100% stable. Most of
the features are untested (both by people and by unit/integration tests) because Chris Hartl implemented
it right before he left, and we're going to need to add tests at some point soon. I added a first
integration test in this commit, but it's just a start.
The fixes include:
1. Stop having the genotyping code strip out AD values. It doesn't make sense that it should do this so
I don't know why it was doing that at all.
Updated GenotypeGVCFs so that it doesn't need to manually recover them anymore.
This also helps CalculateGenotypePosteriors which was losing the AD values.
Updated code in LeftAlignAndTrimVariants to strip out PLs and AD, since it wasn't doing that before.
Updated the integration test for that walker to include such data.
2. Chris was calling Math.pow directly on the normalized posteriors which isn't safe.
Instead, the normalization routine itself can revert back to log scale in a safe manner so let's use it.
Also, renamed the variable to posteriorProbabilities (and not likelihoods).
3. Have CGP update the AC/AF/AN counts after fixing GTs.
commit 5e73b94eed3d1fc75c88863c2cf07d5972eb348b
Merge: e12593a d04a585
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Fri Feb 14 09:25:22 2014 +0000
Merge pull request #1 from broadinstitute/checkpoint
SimpleTimer passes tests, with formatting
commit d04a58533f1bf5e39b0b43018c9db3302943d985
Author: kshakir <github@kshakir.org>
Date: Fri Feb 14 14:46:01 2014 +0800
SimpleTimer passes tests, with formatting
Fixed getNanoOffset() to offset nano to nano, instead of nano to seconds.
Updated warning message with comma separated numbers, and exact values of offsets.
commit e12593ae66a5e6f0819316f2a580dbc7ae5896ad
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Wed Feb 12 13:27:07 2014 +0000
Remove instance of 'Timer'.
commit 47a73e0b123d4257b57cfc926a5bdd75d709fcf9
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Wed Feb 12 12:19:00 2014 +0000
Revert a couple of changes that survived somehow.
- CheckpointableTimer,Timer -> SimpleTimer
commit d86d9888ae93400514a8119dc2024e0a101f7170
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Mon Jan 20 14:13:09 2014 +0000
Revised commits following comments.
- All utility merged into `SimpleTimer`.
- All tests merged into `SimpleTimerUnitTest`.
- Behaviour of `getElapsedTime` should now be consistent with `stop`.
- Use 'TimeUnit' class for all unit conversions.
- A bit more tidying.
commit 354ee49b7fc880e944ff9df4343a86e9a5d477c7
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Fri Jan 17 17:04:39 2014 +0000
Add a new CheckpointableTimerUnitTest.
Revert SimpleTimerUnitTest to the version before any changes were made.
commit 2ad1b6c87c158399ededd706525c776372bbaf6e
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Tue Jan 14 16:11:18 2014 +0000
Add test specifically checking behaviour under checkpoint/restart.
Slight alteration to the checkpointable timer based on observations
during the testing - it seems that there's a fair amount of drift
between the sources anyway, so each time we stop we resynchronise the
offset. Hopefully this should avoid gradual drift building up and
presenting as checkpoint/restart drift.
commit 1c98881594dc51e4e2365ac95b31d410326d8b53
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Tue Jan 14 14:11:31 2014 +0000
Should use consistent time units
commit 6f70d42d660b31eee4c2e9d918e74c4129f46036
Author: Nicholas Clarke <nc6@sanger.ac.uk>
Date: Tue Jan 14 14:01:10 2014 +0000
Add a new timer supporting checkpoint mechanisms.
The issue with this is that the current timer is locked to JVM nanoTime. This can be reset after
a checkpoint/restart and result in negative elapsed times, which causes an error.
This patch addresses the issue in two ways:
- Moves the check on timer information in GenomeAnalysisEngine.java to only occur if a time limit has been
set.
- Create a new timer (CheckpointableTimer) which keeps track of the relation between system and nano time. If
this changes drastically, then the assumption is that there has been a JVM restart owing to checkpoint/restart.
Any time straddling a checkpoint/restart event will not be counted towards total running time.
Signed-off-by: Khalid Shakir <kshakir@broadinstitute.org>
Updated path for output gatkdocs in nightly build script.
Removed patch in plugin manager that contained a workaround for gatkdocs running in the top level directory.
After extensive detective work, Joel determined that these tests were failing
due to changes in the implementation of Math.pow() in newer versions of
Java 1.7.
All GSA members should ensure that they're using a JDK that is at least
as current as the one in the Java-1.7 dotkit on the Broad servers
(build 1.7.0_51-b13).
This change should allow us to test that the GATK jar has been
correctly packaged at release time, by ensuring that only the
packaged jar + a few test-related dependencies are on the classpath
when tests are run.
Note that we still need to actually test that this works as intended
before we can make this live in the Bamboo release plan.
1. AD values now propogate up (they weren't before).
2. MIN_DP gets transferred over to DP and removed.
3. SB gets removed after FS is calculated.
Also, added a bunch of new integration tests for GenotypeGVCFs.
This tool will take any number of gVCFs and create a merged gVCF (as opposed to
GenotypeGVCFs which produces a standard VCF).
Added unit/integration tests and fixed up GATK docs.
New properties to disable regenerating example resources artifact when each parallel test runs under packagetest.
Moved collection of packagetest parameters from shell scripts into maven profiles.
Fixed necessity of test-utils jar by removing incorrect dependenciesToScan element during packagetests.
When building picard libraries, run clean first.
Fixed tools jar dependency in picard pom.
Integration tests properly use the ant-bridge.sh test.debug.port variable, like unit tests.
Story:
https://www.pivotaltracker.com/story/show/65048706https://www.pivotaltracker.com/story/show/65116908
Changes:
ActiveRegionTrimmer in now an argument collection and it returns not only the trimmed down active region but also the non-variant containing flanking regions
HaplotypeCaller code has been simplified significantly pushing some functionality two other classes like ActiveRegion and AssemblyResultSet.
Fixed a problem with the way the trimming was done causing some gVCF non-variant records no have conservative 0,0,0 PLs
JNI. See copied text from email below.
2. This commit contains all the code used in profiling, detecting FP
exceptions, dumping intermediate results. All flagged off using ifdefs,
but it's there.
--------------Text from email
As we discussed before, it's the denormal numbers that are causing the
slowdown - the core executes some microcode uops (called FP assists)
when denormal numbers are detected for FP operations (even un-vectorized
code).
The C++ compiler by default enables flush to zero (FTZ) - when set, the
hardware simply converts denormal numbers to 0. The Java binary
(executable provided by Oracle, not the native library) seems to be
compiled without FTZ (sensible choice, they want to be conservative).
Hence, the JNI invocation sees a large slowdown. Disabling FTZ in C++
slows down the C++ sandbox performance to the JNI version (fortunately,
the reverse also holds :)).
Not sure how to show the overhead for these FP assists easily - measured
a couple of counters.
FP_ASSISTS:ANY - shows number of uops executed as part of the FP
assists. When FTZ is enabled, this is 0 (both C++ and JNI), when FTZ is
disabled this value is around 203540557 (both C++ and JNI)
IDQ:MS_UOPS_CYCLES - shows the number of cycles the decoder was issuing
uops when the microcode sequencing engine was busy. When FTZ is enabled,
this is around 1.77M cycles (both C++ and JNI), when FTZ is disabled
this value is around 4.31B cycles (both C++ and JNI). This number is
still small with respect to total cycles (~40B), but it only reflects
the cycles in the decode stage. The total overhead of the microcode
assist ops could be larger.
As suggested by Mustafa, I compared intermediate values (matrices M,X,Y)
and final output of compute_full_prob. The values produced by C++ and
Java are identical to the last bit (as long as both use FTZ or no-FTZ).
Comparing the outputs of compute_full_prob for the cases no-FTZ and FTZ,
there are differences for very small values (denormal numbers).
Examples:
Diff values 1.952970E-33 1.952967E-33
Diff values 1.135071E-32 1.135070E-32
Diff values 1.135071E-32 1.135070E-32
Diff values 1.135071E-32 1.135070E-32
For this test case (low coverage NA12878), all these values would be
recomputed using the double precision version. Enabling FTZ should be
fine.
-------------------End text from email
These changes happened in Tribble, but Joel clobbered them with his commit.
We can now change the logging priority on failures to validate the sequence dictionary to WARN.
Thanks to Tim F for indirectly pointing this out.
1. Throw a user error when the input data for a given genotype does not contain PLs.
2. Add VCF header line for --dbsnp input
3. Need to check that the UG result is not null
4. Don't error out at positions with no gVCFs (which is possible when using a dbSNP rod)
Joel is working on these failures in a separate branch. Since
maven (currently! we're working on this..) won't run the whole
test suite to completion if there's a failure early on, we need
to temporarily disable these tests in order to allow group members
to run tests on their branches again.
Added pom.xml workarounds for duplicate classpath error, due to gatk-framework dependency containing required BaseTest, and jarred *UnitTest/*IntegrationTest classes that also exist as files under target/test-classes.
Here are the git moved directories in case other files need to be moved during a merge:
git-mv private/java/src/ private/gatk-private/src/main/java/
git-mv private/R/scripts/ private/gatk-private/src/main/resources/
git-mv private/java/test/ private/gatk-private/src/test/java/
git-mv private/testdata/ private/gatk-private/src/test/resources/
git-mv private/scala/qscript/ private/queue-private/src/main/qscripts/
git-mv private/scala/src/ private/queue-private/src/main/scala/
git-mv protected/java/src/ protected/gatk-protected/src/main/java/
git-mv protected/java/test/ protected/gatk-protected/src/test/java/
git-mv public/java/src/ public/gatk-framework/src/main/java/
git-mv public/java/test/ public/gatk-framework/src/test/java/
git-mv public/testdata/ public/gatk-framework/src/test/resources/
git-mv public/scala/qscript/ public/queue-framework/src/main/qscripts/
git-mv public/scala/src/ public/queue-framework/src/main/scala/
git-mv public/scala/test/ public/queue-framework/src/test/scala/
Changes:
-------
<NON_REF> likelihood in variant sites is calculated as the maximum possible likelihood for an unseen alternative allele: for reach read is calculated as the second best likelihood amongst the reported alleles.
When –ERC gVCF, stand_conf_emit and stand_conf_call are forcefully set to 0. Also dontGenotype is set to false for consistency sake.
Integration test MD5 have been changed accordingly.
Additional fix:
--------------
Specially after adding the <NON_REF> allele, but also happened without that, QUAL values tend to go to 0 (very large integer number in log 10) due to underflow when combining GLs (GenotypingEngine.combineGLs). To fix that combineGLs has been substituted by combineGLsPrecise that uses the log-sum-exp trick.
In just a few cases this change results in genotype changes in integration tests but after double-checking using unit-test and difference between combineGLs and combineGLsPrecise in the affected integration test, the previous GT calls were either border-line cases and or due to the underflow.
2. Split into DebugJNILoglessPairHMM and VectorLoglessPairHMM with base
class JNILoglessPairHMM. DebugJNILoglessPairHMM can, in principle,
invoke any other child class of JNILoglessPairHMM.
3. Added more profiling code for Java parts of LoglessPairHMM
Problem:
matchToMatch transition calculation was wrong resulting in transition probabilites coming out of the Match state that added more than 1.
Reports:
https://www.pivotaltracker.com/s/projects/793457/stories/62471780https://www.pivotaltracker.com/s/projects/793457/stories/61082450
Changes:
The transition matrix update code has been moved to a common place in PairHMMModel to dry out its multiple copies.
MatchToMatch transtion calculation has been fixed and implemented in PairHMMModel.
Affected integration test md5 have been updated, there were no differences in GT fields and example differences always implied
small changes in likelihoods that is what is expected.
2. Wrapped _mm_empty() with ifdef SIMD_TYPE_SSE
3. OpenMP disabled
4. Added code for initializing PairHMM's data inside initializePairHMM -
not used yet
SSE compilation warning.
2. Added code to dynamically select between AVX, SSE4.2 and normal C++ (in
that order)
3. Created multiple files to compile with different compilation flags:
avx_function_prototypes.cc is compiled with -xAVX while
sse_function_instantiations.cc is compiled with -xSSE4.2 flag.
4. Added jniClose() and support in Java (HaplotypeCaller,
PairHMMLikelihoodCalculationEngine) to call this function at the end of
the program.
5. Removed debug code, kept assertions and profiling in C++
6. Disabled OpenMP for now.
1. Moved computeLikelihoods from PairHMM to native implementation
2. Disabled debug - debug code still left (hopefully, not part of
bytecode)
3. Added directory PairHMM_JNI in the root which holds the C++
library that contains the PairHMM AVX implementation. See
PairHMM_JNI/JNI_README first
It didn't completely work before (it was hard-coded for a particular long-lost data set) but it should work now.
Since I thought that it might prove useful to others, I moved it to protected and added integration tests.
GERALDINE: NEW TOOL ALERT!
Problem: the codec was written to take in consensus pileups produced with pileup -c option (which consists of 10 or 13 fields per line depending on the variant type) but errored out on the basic pileup format (which only has 6 fields per line). This was inconsistent and confusing to users.
Solution: I added a switch in the parsing to recognize and handle both cases more appropriately, and updated related docs. While I was at it I also improved error messages in CheckPileup, which now emits User Error: Bad Input exceptions when reporting mismatches. Which may not be the best thing to do (ultimately they're not really errors, they're just reporting unwelcome results) but it beats emitting Runtime Exceptions.
Tested by CheckPileupIntegrationTest which tests both format cases.
-Added docs for ERC mode in HC
-Move RecalibrationPerformance walker since to private since it is experimental and unsupported
-Updated VR docs and restored percentBad/numBad (but @Hidden) to enable deprecation alert if users try to use them
-Improved error msg for conflict between per-interval aggregation and -nt
-Minor clean up in exception docs
-Added Toy Walkers category for devs and dev supercat (to build out docs for developers)
-Added more detailed info to GenotypeConcordance doc based on Chris forum post
-Added system to include min/max argument values in gatkdocs (build gatkdocs with 'ant gatkdocs' to test it, see engine and DoC args for in situ examples)
-Added tentative min/max argument annotations to DepthOfCoverage and CommandLineGATK arguments (and improved docs while at it)
-Added gotoDev annotation to GATKDocumentedFeature to track who is the go-to person in GSA for questions & issues about specific walkers/tools (now discreetly indicated in each gatkdoc)
To do this I have added a RodBindingCollection which can represent either a VCF or a
file of VCFs. Note that e.g. SelectVariants allows a list of RodBindingCollections so
that one can intermix VCFs and VCF lists.
For VariantContext tags with a list, by default the tags for the -V argument are applied
unless overridden by the individual line. In other words, any given line can have either
one token (the file path) or two tokens (the new tags and the file path). For example:
foo.vcf
VCF,name=bar bar.vcf
Note that a VCF list file name must end with '.list'.
Added this functionality to CombineVariants, CombineReferenceCalculationVariants, and VariantRecalibrator.
For example, this tool can be used for processing bowtie RNA-seq data.
Each read with k N-cigar elemments is plit to k+1 reads. The split is done by hard clipping the bases rest of the bases.
In order to do it, few changes were introduced to some other clipping methods:
- make a segnificant change in ClippingOp.hardClip() that prevent the spliting of read with cigar: 1M2I1N1M3I.
- change getReadCoordinateForReferenceCoordinate in ReadUtil to recognize Ns
create unitTests for that walker:
- change ReadClipperTestUtils to be more general in order to use its code and avoid code duplication
- move some useful methods from ReadClipperTestUtils to CigarUtils
create integration test for that class
small change in a comment in FullProcessingPipeline
last commit:
Address review comments:
- move to protected under walkers/rnaseq
- change the read splitting methods to be more readable and more efficiant
- change (minor changes) some methods in ReadClipper to allow the changes in split reads
- add (minor change) one method to CigarUtils to allow the changes in split reads
- change ReadUtils.getReadCoordinateForReferenceCoordinate to include possible N in the cigar
- address the rest of the review comments (minor changes)
- fix ReadUtilsUnitTest.testReadWithNs acoording to the defult behaviour of getReadCoordinateForReferenceCoordinate (in case of refernce index that fall into deletion, return the read index of the base before the deletion).
- add another test to ReadUtilsUnitTest.testReadWithNs
- Allow the user to print the split positions (not working proparly currently)
* add overall walker GATKDocs
* add explanation for skip parameter and make it advanced
* reverse the logic on exculding unmapped reads for clarity
* fix read length calculation to no longer include indels
ps: I am not sure how useful this walker is (I didn't write it) but the skip logic is poor and
calculates the entire statistic for the reads it is eventually going to skip. This would be an easy
fix, but only worth our time if people actually use this.
The update contains:
1. documentation changes for VariantContext and Allele (which used to discuss the now obsolete null allele)
2. better error messages for VCFs containing complex rearrangements with breakends
3. instead of failing badly on format field lists with '.'s, just ignore them
Also, there is a trivial change to use a more efficient method to remove a bunch of attributes from a VC.
Delivers PT#s 59675378, 59496612, and 60524016.
Basically, it does 3 things (as opposed to having to call into 3 separate walkers):
1. merge the records at any given position into a single one with all alleles and appropriate PLs
2. re-genotype the record using the exact AF calculation model
3. re-annotate the record using the VariantAnnotatorEngine
In the course of this work it became clear that we couldn't just use the simpleMerge() method used
by CombineVariants; combining HC-based gVCFs is really a complicated process. So I added a new
utility method to handle this merging and pulled any related code out of CombineVariants. I tried
to clean up a lot of that code, but ultimately that's out of the scope of this project.
Added unit tests for correctness testing.
Integration tests cannot be used yet because the HC doesn't output correct gVCFs.
-You can now add "minValue", "maxValue", "minRecommendedValue", and "maxRecommendedValue" attributes
to @Argument annotations for command-line arguments
-"minValue" and "maxValue" specify hard limits that generate an exception if violated
-"minRecommendedValue" and "maxRecommendedValue" specify soft limits that generate a warning if violated
-Works only for numeric arguments (int, double, etc.) with @Argument annotations
-Only considers values actually specified by the user on the command line, not default values
assigned in the code
As requested by Geraldine
In general, test classes cannot use 3rd-party libraries that are not
also dependencies of the GATK proper without causing problems when,
at release time, we test that the GATK jar has been packaged correctly
with all required dependencies.
If a test class needs to use a 3rd-party library that is not a GATK
dependency, write wrapper methods in the GATK utils/* classes, and
invoke those wrapper methods from the test class.
Previously, we would strip out the PLs and AD values since they were no longer accurate. However, this is not ideal because
then that information is just lost and 1) users complain on the forum and post it as a bug and 2) it gives us problems in both
the current and future (single sample) calling pipelines because we subset samples/alleles all the time and lose info.
Now the PLs and AD get correctly selected down.
While I was in there I also refactored some related code in subsetDiploidAlleles(). There were no real changes there - I just
broke it out into smaller chunks as per our best practices.
Added unit tests and updated integration tests.
Addressed reviews.
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.
-- Added 'jobRunnerJobName' definition to QFunction, defaults to value of shortDescription
-- Edited Lsf and Drmaa JobRunners to use this string instead of description for naming jobs in the scheduler
Signed-off-by: Joel Thibault <thibault@broadinstitute.org>
We have generalized the processing script to be able to handle multiple scenarios. Originally it was
designed for PCR free data only, we added all the steps necessary to start from fastq and process
RNA-seq as well as non-human data. This is our go to script in TechDev.
* add optional "starting from fastq" path to the pipeline
* add mark duplicates (optionally) to the pipeline
* add an option to run with the mouse data (without dbsnp and with single ended fastq)
* add option to process RNA-seq data from topHat (add RG and reassign mapping quality if necessary)
* add option to filter or include reads with N in the cigar string
* add parameter to allow keeping the intermediate files
-- We use the RegenotypeVariants walker to recompute the qual field. (instead of the discussed idea of adding this functionality to CombineVariants)
-- QualByDepth will now be recomputed even if the stratified contexts are missing. This greatly improves the QD estimate for this pipeline. Doesn't work for multi-allelics since the qual can't be recomputed.
--Previously it gave a cryptic message:
----IO error while decoding blarg.script with UTF-8
----Please try specifying another one using the -encoding option
this script downsamples an exome BAM several times and makes a coverage distribution
analysis (of bases that pass filters) as well as haplotype caller calls with a NA12878
Knowledge Base assessment with comparison against multi-sample calling
with the UG.
This script was used for the "downsampling the exome" presentation
Quick fix the missing column header in the QualifyMissingIntervals
report.
Adding a QScript for the tool as well as a few minor updates to the
GATKReportGatherer.
--specifying exception types in cases where none was already specified
----mostly changed to catch Exception instead of Throwable
----EmailMessage has a point where it should only be expecting a RetryException but was catching everything
--changing build.xml so that it prints scala feature warning details
--added necessary imports needed to remove feature warnings
--updating a newly deprecated enum declaration to match the new syntax
David Roazen
Eric Banks
Alec Wysoker
Khalid Shakir
Valentin Ruano-Rubio
Ami Levy-Moonshine
Karthik Gururaj
Laura Gauthier
Joel Thibault
Chris Whelan
pdexheimer
Ryan Poplin
kshakir
Nicholas Clarke
skashin
mghodrat
Yossi Farjoun
Geraldine Van der Auwera
Menachem Fromer
Mauricio Carneiro
Chris Hartl
bradtaylor
Louis Bergelson
Chris Hartl
Michael McCowan