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
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.
-- 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
David Roazen
Ryan Poplin
Eric Banks
Guillermo del Angel
Matt Hanna
Mauricio Carneiro
Mark DePristo
Christopher Hartl