The ClippingOp clip cigar function would run into a endless loop if the parameter were out of the reads range, I stopped the bug.
* There is no check to make sure the read coordinate are covered by the read though
When Hard clipping to interval, I added a check for deletions.
NOTE: method works for NA12878 WEx but needs to be more thoroughly tested/optimized
After discussing this with Mark, it seems clear that the old version of the
VariantEval FunctionalClass stratification is preferable to this version.
By reverting, we maintain backwards compatibility with legacy output files
from the old GenomicAnnotator, and can add SnpEff support later without
breaking that backwards compatibility.
This reverts commit b44acd1abd9ab6eec37111a19fa797f9e2ca3326.
This is a temporary and hopefully short-lived solution. I've modified
the FunctionalClass stratification to stratify by effect impact as
defined by SnpEff annotations (high, moderate, and low impact) rather
than by the silent/missense/nonsense categories.
If we want to bring back the silent/missense/nonsense stratification,
we should probably take the approach of asking the SnpEff author
to add it as a feature to SnpEff rather than coding it ourselves,
since the whole point of moving to SnpEff was to outsource genomic
annotation.
-Rewrote SnpEff support in VariantAnnotator to support the latest SnpEff release (version 2.0.2)
-Removed support for SnpEff 1.9.6 (and associated tribble codec)
-Will refuse to parse SnpEff output files produced by unsupported versions (or without a version tag)
-Correctly matches ref/alt alleles before annotating a record, unlike the previous version
-Correctly handles indels (again, unlike the previous version
-- Cannot reproduce the very long waits reported by some users.
-- Fixed problem that exception might result in an undeleted file, which is now fixed with deleteOnExit()
All VariantAnnotator annotation classes may now have an (optional) initialize() method
that gets called by the VariantAnnotatorEngine ONCE before annotation starts.
As an example of how this can be used, the SnpEff annotation class will use the initialize()
method to check whether the SnpEff version number stored in the vcf header is a supported
version, and also to verify that its required RodBinding is present.
b) Added (but left commented out since it may affect integration tests and to isolate commits) fix to per-sample DP reporting, so that deletions are included in count.
c) Bug fix to avoid having non-reference genotypes assigned to samples with PL=0,0,0. Correct behavior should be to no-call these samples, and to ignore these samples when computing AC distribution since their likelihoods are not informative.
-- Support for streaming VCF writing via the VCFWriter interface
-- GCF now has a header and a footer. The header is minimal, and contains a forward pointer to the position of the footer in the file.
-- Readers now read the header, and then jump to the footer to get the rest of the "header" information
-- Version now a field in GCF
-- per sample stratification was not being calculated correctly. The alt allele was always remaining, even if the genotype of the sample was hom-ref. Although conceptually fine, this breaks the assumptions of all of the eval modules, so per sample stratifications actually included all variants for everything. Eric is going to fix the system in general, so this commit may break the build.
-- ArrayList are List where possible
-- states refactored into VariantStratifier base class (reduces many lines of duplicate code)
-- Added VariantType stratification that partitions report by VariantContext.Type
- Instead of using readLength, the ReadUtil function are used to get a proper read coordinate
- Added debug info in interval clipping ( with -dl)
NOTE: method might not be safe for production and checks need to be added to the ClippingOp code
Updates for HybridSelectionPipeline:
- Use VQSR on SNPs for projects using bait set whole_exome_agilent_1 and applying cut at 98.5.
- If a whole_exome_agilent_1 project has less than 50 samples also mixing in 1000G samples to reach VQSR thresholds.
- Updated SNP hard filters based on analysis done with ebanks to approximate VQSR results on small target batches.
- Removed GSA_PRODUCTION_ONLY flag from indel caller.
- Updated indel hard filters based on delangel's analysis.
- Updated HybridSelectionPipelineTest to use HARD SNP filters only, for now.
-- Very minimal working version that can read / write binary VCFs with genotypes
-- Already 10x faster for sites, 5x for fully parsed genotypes, and 1000x for skipping genotypes when reading
-- Removed versions getAttribriteAsX(key) that except on not having the value.
-- Removed version that getAttributeAsXNoException(key)
-- The only available assessors are now getAttributeAsX(key, default).
-- This single accessors properly handle their argument types, so if the value is a double it is returned directly for getAttributeAsDouble(), or if it's a string it's converted to a double. If the key isn't found, default is returned.
-- Don't create an empty LinkedHashSet() for PASS fields. Just return Collections.emptySet() instead.
-- For filter fields with actual values, returns an unmodifiableSet instead of one that can be changed
Roger Zurawicki
Guillermo del Angel
Menachem Fromer
Christopher Hartl
David Roazen
Eric Banks
Ryan Poplin
Mark DePristo
Matt Hanna
Mauricio Carneiro
Khalid Shakir