1. Add dbsnp RS ID to VCF output from genotyper; to do this I needed to fix the dbsnp rod which did not correctly return this value.
2. Remove AlleleBalanceBacked and instead generalize the arbitrary info fields backing VCFs (and potentially others) in preparation for refactoring VariantFiltration next week.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2028 348d0f76-0448-11de-a6fe-93d51630548a
-Don't restrict info fields to 2-letter keys
[about to move these to core]
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2002 348d0f76-0448-11de-a6fe-93d51630548a
-Improvement to snp genotype concordance test
And with that, it looks like I get revision #2000.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2000 348d0f76-0448-11de-a6fe-93d51630548a
Procedure:
1. Sites that are likely homozygous-variant but are called as heterozygous are identified.
2. For each site and read group, we compute the proportion of bases in the pileup supporting an alternate allele.
3. A one-sample, left-tailed t-test is performed with the null hypothesis being that the alternate allele distribution has a mean of 0.95 and the alternate hypothesis being that the true mean is statistically significantly less than expected (pValue < 1e-9).
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Now PooledConcordance and GenotypeConcordance inherit from the same super class (and can therefore share data structures and functionality). Also, they now use ConcordanceTruthTable to keep track of necessary info.
GenotypeConcordance passes integration tests.
PooledConcordance needs to be finished by Chris.
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It needs to be modified a bit and then hooked up to a pooled model, but that is now possible.
At this point, there is no difference to the Unified Genotyper.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1978 348d0f76-0448-11de-a6fe-93d51630548a
Now, all output is generalized and all of the intelligence lies where it is supposed to.
Next stage is syncing up old and new models and making sure we're outputting exactly what we should.
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-Make rods return the appropriate type of Genotype calls from getGenotype().
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One can now split up any number of sets into an N-way Venn (although it doesn't check for discordance in the calls, so you'll still want to use SimpleVenn for 2-way comparisons).
Wiki docs are updated.
To do: update to use Ryan's generic hash map when it's ready for public use.
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-Do the right thing in all models for all-base-mode (for Kiran).
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CallsetConcordance now gets possible concordance types by looking at classes that implement ConcordanceType instead of having them hard-coded in.
Thanks to Kiran this was pretty easy...
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Some things still need to be changed, but it will entail some more design decisions first (which means I get to bug M&A again tomorrow!).
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BTTJ - remove 'N's from previous base analysis -- even if both read and ref are 'N' (which does happen, occasionally)
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Integration test comment changed to reflect actual date of last md5 update.
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VariantEvalWalker - whoops, wrote PooledGenotypeAnalysis rather than PooledAnalysis, now passes tests again
- PooledFrequencyAnalysis - don't bother initializing matrices if this isn't a pool
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+ Changes to doc
@ BasicPoolVariantAnalysis
+ use char rather than ReferenceContext
+ calculate # alleles
@ PooledFrequencyAnalysis
+ breakdown of call metrics by estimated number of alleles in pool
@ VariantEvalWalker
+ add PooledFrequencyAnalysis to analysis set
@ PooledGenotypeConcordance
+ correctly calculate maximal allele frequency for output
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Changed BaseTransitionTable to comparable objects for consistent ordering of output
( e.g. so the integration test doesn't yell so much )
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@ Pooled utils & power
- Removed two of the power walkers leaving only PowerBelowFrequency, added some additional
flags on PowerBelowFrequency to give it some of the behavior that PowerAndCoverage had
- Removed a number of PoolUtils variables and methods that were used in those walkers or simply
not used
- Removed AnalyzePowerWalker (un-necessary)
- Changed the location of Quad/Squad/ReadOffsetQuad into poolseq
@NQS
- Deleted all walkers but the minimum NQS walker, refactored not to use LocalMapType
@ BaseTransitionTable
- Added a slew of new integration tests for different flaggable and integral parameters
- (Scala) just a System.out that was added and commented out (no actual code change)
- (Java) changed a < to <= and a boolean formula
Chris
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@PoolUtils - split reads by indel/simple base
@BaseTransitionTable - complete refactoring, nicer now
@UnifiedArgumentCollection - added PoolSize as an argument
@UnifiedGenotyper - checks to ensure pooled sequencing uses the appropriate model
@GenotypeCalculationModel - instantiates with the new PoolSize argument
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Also moved a buch of Lists over to Sets for consistancy.
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also: their, I hope your happy Eric, from now on I'll try not to flout my awesomest grammer in the future accept when I need to illicit a strong response :-)
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We need to filter contexts in that case since the calling walkers don't get UG's traversal-level filters.
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Remove all sequenom stuff from the FastaAlternateReferenceMaker so it can just concentrate on making alternate references...
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Only print out positions with at least one non-ref call
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I have previous revision to revert back to.
This is a calculator that will calculate:
P[ True base is X | read base mismatches, secondary base is Y, previous K bases are Z1,Z2,...ZK ]
where the number of pervious reference bases to take into account is user-defined. The secondary base is optional as well.
--usePreviousBases k
tells the walker to use the k previous reference bases in the transition table
--useSecondaryBase
tells the walker to use the secondary base at a locus in the transition table
these can be used together.
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Also a little playground walker that changes the sort order flag of a BAM file.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1805 348d0f76-0448-11de-a6fe-93d51630548a
Locus Power_for_k_alleles Power_for_k-2_alleles Power_for_k-2_alleles ... Power_for_1_allele
This was a request from Jason Flannick & the T2DB group.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1786 348d0f76-0448-11de-a6fe-93d51630548a
CalculateBaseLikelihoodsWalker.java walks through reads calculates likelihoods using SSG at each base position
CalculateAlleleLikelihoodsWalker.java walks through HLA dictionary and calculates likelihoods for allele pairs given output of CalculateBaseLikelihoodsWalker.java
CalculatePhaseLikelihoodsWalker.java walks through reads and calculates likelihoods score for allele pairs given phase information
File Readers:
BaseLikelihoodsFileReader.java reads text file of likelihoods outputted by SSG
FrequencyFileReader.java reads text file of HLA allele frequencies
PolymorphicSitesFileReader.java reads text file of polymorphic sites in the HLA dictionary
SAMFileReader.java reads a sam file (used to read HLA dictionary when in another walker)
SimilarityFileReader.java reads a text file of how similar each read is to the closest HLA allele (used to filter misaligned reads)
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1744 348d0f76-0448-11de-a6fe-93d51630548a
@ PooledGenotypeConcordance - changes to output, now also reports false-negatives and false-positives as interesting sites. It's been like this in my directory for ages, just never committed.
@NQSExtendedGroupsCovariantWalker - change for formatting.
@NQSTabularDistributionWalker - breaks out the full (window_size)-dimensional empirical error rate distribution by the window. So if you've got a window of size 3; the quality score sequences 22 25 23 and 22 25 24 have their own bins (each of the 40^3 sequences get one) for match and mismatch counts.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1730 348d0f76-0448-11de-a6fe-93d51630548a
quality score of a particular base is than the quality score of its neighbors. The granularity of the binning
jumps from 32 groups to 860 groups.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1702 348d0f76-0448-11de-a6fe-93d51630548a
Also, sanity check that ref is not 'N'.
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- summary output now reported as a percentage rather than proportion; 2 sigfigs
- fixed minor bug where FNR was calculated over total calls rather than total variant sites
- column headers are_now_contiguous_strings
- spacing fixed
- "No Call" separated from "Ref Call" as its own column
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1644 348d0f76-0448-11de-a6fe-93d51630548a
Additional output & better output formatting. It has now undergone a good five hours of testing; and for pools of size 1 outputs exactly the same statistics as GenotypeConcordance (when GenotypeConcordance is modified to do nothing on reference='N'); and for pools of many sizes outputs close to the expected (by genetics) statistics. Looks like this is working properly.
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Deletion: PooledGenotypeConcordanceNew
Rewrite: PooledGenotypeConcordance. It works, and is blazing fast compared to the earlier version (1 order of magnitude speedup)! And is now entirely non-hackey, as opposed to before when there were some hacky bits.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1640 348d0f76-0448-11de-a6fe-93d51630548a
Iterates synchronously over two (name-ordered) single-end alignment SAM files with, possibly, multiple alignments per read and for each read name encountered returns pairs<all alignments for end1, all alignments for end2>
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1639 348d0f76-0448-11de-a6fe-93d51630548a
@PooledGenotypeConcordanceNew - a new version of the pooled genotype concordance test for Variant Eval. Code altered to be more extensible, use a private class for handling the count tables so it doesn't gunk up the code in the test itself, and for easy debugging. The hackier methods from the original were rewritten properly. Currently computes more statistics that it outputs. Code compiles, is never called by anything, and breaks none of the tests.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1632 348d0f76-0448-11de-a6fe-93d51630548a
@NQSMismatchCovariantWalker - Walks along the gene calculating the table
# NQS
# Q score
# mismatches at non-dbsnp sites
# total number of bases at non-dbsnp sites
And prints it out at the end.
Changes:
@PooledGenotypeConcordance now works. Takes a path to a file listing a bunch of hapmap IDs in whatever pool we want to check, reads those in, and checks for concordance by name.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1614 348d0f76-0448-11de-a6fe-93d51630548a
but mostly altering the code so it's much more readable and understandable, and much less hacky-looking.
ADDED:
@Quad: This is just like Pair, except with four fields. In the original CoverageAndPowerWalker I often used
a pair of pairs to hold things, which made the code nigh unreadable.
@SQuad: An extension of Quad for when you want to store objects of the same type. Let's you simply declare
new SQuad<X> rather than new Quad<X,X,X,X>
@ReadOffsetQuad: An extension of Quad specifically for holding two lists of reads and two lists of offsets
Supports construction from AlignmentContexts and conversion to AlignmentContexts (given
a GenomeLoc). There are methods that make it very clear what the code is doing (getSecondRead()
rather than the cryptic getThird() )
@PowerAndCoverageWalker: The new version of CoverageAndPowerWalker. If the tests all go well, then I'll remove
the old version. New to this version is the ability to give an output file directly
to the walker, so that locus information prints to the file, while the final reduce
prints to standard out. Bootstrap iterations are now a command line argument rather
than a final int; and users can instruct the walker to print out the coverage/power
statistics for both the original reads, and those reads whose quality score exceeds
a user-defined threshold.
CHANGES:
@PoolUtils: Altered methods to accept as argumetns, and return, Quad objects. Added a random partition method
for bootstrapping.
@CoverageAndPowerWalker: Altered methods to work with the new PoolUtils methods.
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Rollback of Variant-related changes of r1585, additional PGC code
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@VariantEvalWalker - added a command line option to input a file path to a pooled call file for pooled genotype concordance checking. This string is to be passed to the PooledGenotypeConcordance object.
@AllelicVariant - added a method isPooled() to distinguish pooled AllelicVariants from unpooled ones.
@ all the rest - implemented isPooled(); for everything other than PooledEMSNProd it simply returns false, for PooledEMSNProd it returns true.
Added:
@PooledGenotypeConcordance - takes in a filepath to a pool file with the names of hapmap individuals for concordance checking with pooled calls
and does said concordance checking over all pools. Commented out as all the methods are as yet unwritten.
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After consulting our resident expert (Aaron), we're going to (temporarily) remove the date from the vcf output until we can come up with a better solution. However, this shouldn't cause any short-term problems because the data truly is optional.
VF test's MD5s are updated.
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1. VariantsToVCF can now be called statically to output VCF for a single ROD instance; this is temporary until we have a VCF ROD.
2. VariantFiltration now outputs only 2 files, both mandatory: all variants that pass filters in geli text, and all variants in VCF.
If there are any problems, go find Aaron.
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@CoverageAndPowerWalker - removed a hanging colon that was being printed after the reference position
@VariantEvalWalker - added a command line argument for pool size for eventual use in doing pooled caller evaluations. As now, the variable is unused.
@AlignmentContext - altered the scope of class variables from private to protected in order that child objects might have access to them
New Additions:
Filtered Contexts
Sometimes we want to filter or partition reads by some aspect (quality score, read direction, current base, whatever) and use only those reads as
part of the alignment context. Prior to this I've been doing the split externally and creating a new AlignmentContext object. This new approach makes
it a bit easier, as each of these objects are children of AlignmentContext, and can be instantiated from a "raw" AlignmentContext.
@FilteredAlignmentContext is an abstract class that defines the behavior. The abstract method 'filter' is called on the input AlignmentContext, filtering
those reads and offsets by whatever you can think of. The filtered reads/offsets are then maintained in the reads and offsets fields. These classes can
be passed around as AlignmentContexts themselves. Writing a new kind of read-filtered alignment context boils down to implementing the filter method.
@ReverseReadsContext - a FilteredAlignmentContext that takes only reads in the reverse direction
@ForwardReadsContext - a FilteredAlignmentContext that takes only reads in the forward direction
@QualityScoreThresholdContext - a FilteredAlignmentContext that takes only reads above a given quality score threshold (defaults to 22 if none provided).
A unit test bamfile and associated unit tests for these are in the works.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1559 348d0f76-0448-11de-a6fe-93d51630548a
Also fixed the case where MD5 sums had leading zero's clipped off
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1) Moved various disparate concordance / set splitting functionalities to a new parent tool which works like VariantFiltration (i.e. people can write various modules that fit inside and can be run though it).
2) Fixed up argument parsing in VariantFiltration to use key=value format so we don't accidentally mox up values (like I had been doing).
3) Have indel rod print samples
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1540 348d0f76-0448-11de-a6fe-93d51630548a
-Remove KGenomesSNPROD
-Remove rodFLT
-Renamed rodGFF to RodGenotypeChipAsGFF
-Fixed a problem in SSGenotypeCall
-Added basic SSGenotype Test class
-Make VCFHeader constructors public
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1536 348d0f76-0448-11de-a6fe-93d51630548a
I'll move this all to core in a bit...
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This code eventually needs to end up in the VariantFiltration system - when we are ready to parameterize on the fly.
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| Added items |
---------------
@/varianteval/PoolAnalysis
Interface to identify variant analyses that are pool-specific.
@/varianteval/BasicPoolVariantAnalysis
Nearly the same as BasicVariantAnalysis with the addition of a protected integer (numIndividualsInPool)
which holds the pool size. One soulcrushing change is that "protected String filename" needed to
become "protected String[] filename" since now multiple truth files may be looked at. It was tempting
to make the change in BasicVariantAnalysis with some default methods that would maintain usability of
the remainder of the VariantAnalysis objects, but I decided to hold off. We can always merge these
together later.
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Doesn't work yet; same command I used to use now causes GATK to throw an exception.
Will check with Matt & Aaron tomorrow, then do a regression test.
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Also, it's safer to let colt do the log factorial calculations for us.
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The user is warned if a locus exceeds this threshold, and no more reads are added.
Also CombineDup walker had an incorrect package name.
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This now allows us to incorporate both the clustered SNP filter and a SNP-near-indels filter, which otherwise wasn't possible.
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@MathUtils - added a new method: cumBinomialProbLog which calculates a cumulant from any start point to any end point using the BinomProbabilityLog calculation.
@PoolUtils - added a new utility class specifically for items related to pooled sequencing. A major part of the power calculation is now to calculate powers
independently by read direction. The only method in this class (currently) takes your reads and offsets, and splits them into two groups
by read direction.
@CoverageAndPowerWalker - completely rewritten to split coverage, median qualities, and power by read direction. Makes use of cumBinomialProbLog rather than
doing that calculation within the object itself.
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Minor changes to CoverageAndPowerWalker bootstrapping (faster selection of indeces).
Entirely new Aritifical Pool Walker (ArtificialPoolWalkerMk2), will likely replace ArtificialPoolWalker on the next commit. Adapted the method of sampling, and added a helper context class: ArtificialPoolContext which carries much of the burden of calculation and data handling for the walker. The walker itself maps and reduces ArtificialPoolContexts.
Cheers!
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binomialProbabilityLog uses a log-space calculation of the
binomial pmf to avoid the coefficient blowing up and thus
returning Infinity or NaN (or in some very strange cases
-Infinity). The log calculation compares very well, it seems
with our current method. It's in MathUtils but could stand
testing against rigorous truth data before becoming standard.
Added median calculator functions to ListUtils
getQScoreMedian is a new utility I wrote that given reads and
offsets will find the median Q score. While I was at it, I wrote
a similar method, getMedian, which will return the median of any
list of Comparables, independent of initial order. These are in
ListUtils.
Added a new poolseq directory and three walkers
CoverageAndPowerWalker is built on top of the PrintCoverage walker
and prints out the power to detect a mutant allele in a pool of
2*(number of individuals in the pool) alleles. It can be flagged
either to do this by boostrapping, or by pure math with a
probability of error based on the median Q-score. This walker
compiles, runs, and gives quite reasonable outputs that compare
visually well to the power calculation computed by Syzygy.
ArtificialPoolWalker is designed to take multiple single-sample
.bam files and create a (random) artificial pool. The coverage of
that pool is a user-defined proportion of the total coverage over
all of the input files. The output is not only a new .bam file,
but also an auxiliary file that has for each locus, the genotype
of the individuals, the confidence of that call, and that person's
representation in the artificial pool .bam at that locus. This
walker compiles and, uhh, looks pretty. Needs some testing.
AnalyzePowerWalker extends CoverageAndPowerWalker so that it can read previous power
calcuations (e.g. from Syzygy) and print them to the output file as well for direct
downstream comparisons.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1460 348d0f76-0448-11de-a6fe-93d51630548a
This is useful when producing Sequenom input files for validating indels...
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Picard has such a tool but it is geared towards their pipeline and requires intimate knowledge of the lanes/flowcells,etc. This is just easy.
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Also: do not die if alignment record does not have NM tags (but mapping quality will not be recomputed after remapping/reducing for the lack of required data)
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1411 348d0f76-0448-11de-a6fe-93d51630548a
- added first version of a more complicated reference maker which takes in RODs and creates an alternative reference based on the variants (indels and/or SNPs)
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1409 348d0f76-0448-11de-a6fe-93d51630548a
* splitting off only start or end of the read, or both; the output will contain
chopped sequences AND corresponding base qualities
* splitting arbitrary number of bases off each end (different numbers
for left and right segments can be specified; segments can overlap)
* splitting only unmapped reads, ignoring mapped ones
* writing splitted ends into separate sam/bam files, or into a single output file
* decorating original read names with user-specified suffixes for each end
(e.g. _1 and _2 for left and right parts of the read); default: no decoration,
original read names are used
* when mapped reads are split, the alignment cigars are chopped appropriately
and the alignment start positions are adjusted (for the right end) to correctly
specify the alignment of the selected part of the read
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1402 348d0f76-0448-11de-a6fe-93d51630548a
-Set some reasonable defaults (based on pilot2)
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1388 348d0f76-0448-11de-a6fe-93d51630548a
from an array of bases to an object (ReferenceContext), and LocusContext has been renamed to reflect
the fact that it contains contextual information only about the alignments, not the locus in general.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1376 348d0f76-0448-11de-a6fe-93d51630548a
-move out isHet test to GenotypeUtils so all can use it
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1369 348d0f76-0448-11de-a6fe-93d51630548a
- make the filters brainless in that they strictly have thresholds and filter based on them; require user to calculate and input these thresholds.
- update filters in preparation for migration to new output format
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1363 348d0f76-0448-11de-a6fe-93d51630548a
Note that nothing was changed for dnSNP/hapmap priors (not sure what we want to do with these yet - any thoughts?)
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1342 348d0f76-0448-11de-a6fe-93d51630548a
- fixed math bug (pValue needs to be initialized to pCutoff, not 0)
- perform factorial calculations in log space so that huge numbers don't explode
- cache factorial calculations so that each value needs to be computed just once for any given instance of the filter
I've tested it against R and it has held up so far...
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1341 348d0f76-0448-11de-a6fe-93d51630548a
sources and post-construction validation back into the GATKEngine, leaving the MicroScheduler
to just microschedule.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1336 348d0f76-0448-11de-a6fe-93d51630548a
- SSG is much simpler now
- GeliText has been added as a GenotypeWriter
- AlleleFrequencyWalker will be deleted when I untangle the AlleleMetric's dependance on it
- GenotypeLikelihoods now implements GenotypeGenerator, but could still use cleanup
There is still a lot more work to do, but this is a good initial check-in.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1335 348d0f76-0448-11de-a6fe-93d51630548a
rough initial implementation, but should provide enough support so that people can stop
creating SAMFileWriters in reduceInit.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1332 348d0f76-0448-11de-a6fe-93d51630548a
-variants need a length method (can't assume it's a SNP)!
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1324 348d0f76-0448-11de-a6fe-93d51630548a
2. free DB coverage from isSNP restriction
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1322 348d0f76-0448-11de-a6fe-93d51630548a
the string (unfortunately) needs to be sorted for lookup in the table (otherwise we throw a NullPointerException)
TO DO: have the table be smarter instead of sorting each genotype string
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1298 348d0f76-0448-11de-a6fe-93d51630548a
inspecting the source tree and loading walkers, rather than trying to roll
our own by hand.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1286 348d0f76-0448-11de-a6fe-93d51630548a
the RODs it sees. This is the easiest solution to get around the (temporary)
bug of reads being seen multiple times by reads walkers when close intervals
are passed to them (i.e. process full contigs and then use a ref walker to
filter the ones within your intervals of choice)
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1273 348d0f76-0448-11de-a6fe-93d51630548a
This should work, although I need to test it with some real GLFs
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1265 348d0f76-0448-11de-a6fe-93d51630548a
Yes, the name is retarded, but I'm under pressure here...
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1258 348d0f76-0448-11de-a6fe-93d51630548a
rpoplin
mmelgar
ebanks
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depristo
jmaguire
chartl
aaron
sjia
andrewk
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