Hi.
I'm having trouble with ASEReadCounter, the output is empty, there's only the header containing the names of the columns.
The log is this:

20:43:53.002 INFO  ASEReadCounter - Start Date/Time: 24 de outubro de 2018 20:43:45 BRST
20:43:53.002 INFO  ASEReadCounter - ------------------------------------------------------------
20:43:53.002 INFO  ASEReadCounter - ------------------------------------------------------------
20:43:53.003 INFO  ASEReadCounter - HTSJDK Version: 2.16.1
20:43:53.003 INFO  ASEReadCounter - Picard Version: 2.18.13
20:43:53.003 INFO  ASEReadCounter - HTSJDK Defaults.COMPRESSION_LEVEL : 2
20:43:53.003 INFO  ASEReadCounter - HTSJDK Defaults.USE_ASYNC_IO_READ_FOR_SAMTOOLS : false
20:43:53.003 INFO  ASEReadCounter - HTSJDK Defaults.USE_ASYNC_IO_WRITE_FOR_SAMTOOLS : true
20:43:53.003 INFO  ASEReadCounter - HTSJDK Defaults.USE_ASYNC_IO_WRITE_FOR_TRIBBLE : false
20:43:53.003 INFO  ASEReadCounter - Deflater: IntelDeflater
20:43:53.003 INFO  ASEReadCounter - Inflater: IntelInflater
20:43:53.004 INFO  ASEReadCounter - GCS max retries/reopens: 20
20:43:53.004 INFO  ASEReadCounter - Requester pays: disabled
20:43:53.004 INFO  ASEReadCounter - Initializing engine
20:43:53.383 INFO  FeatureManager - Using codec VCFCodec to read file file:///home/nalu/macaco/input_varscan/variantes/vcf_E13_1
20:43:53.405 INFO  ASEReadCounter - Done initializing engine
20:43:53.406 INFO  ProgressMeter - Starting traversal
20:43:53.406 INFO  ProgressMeter -        Current Locus  Elapsed Minutes        Loci Processed      Loci/Minute
20:43:58.672 INFO  ASEReadCounter - 2328384 read(s) filtered by: (((((((ValidAlignmentStartReadFilter AND ValidAlignmentEndReadFilter) AND HasReadGroupReadFilter) AND MatchingBasesAndQualsReadFilter) AND SeqIsStoredReadFilter) AND NotDuplicateReadFilter) AND NotSecondaryAlignmentReadFilter) AND MappedReadFilter)
  2328384 read(s) filtered by: ((((((ValidAlignmentStartReadFilter AND ValidAlignmentEndReadFilter) AND HasReadGroupReadFilter) AND MatchingBasesAndQualsReadFilter) AND SeqIsStoredReadFilter) AND NotDuplicateReadFilter) AND NotSecondaryAlignmentReadFilter)
      2328384 read(s) filtered by: (((((ValidAlignmentStartReadFilter AND ValidAlignmentEndReadFilter) AND HasReadGroupReadFilter) AND MatchingBasesAndQualsReadFilter) AND SeqIsStoredReadFilter) AND NotDuplicateReadFilter)
          2328384 read(s) filtered by: ((((ValidAlignmentStartReadFilter AND ValidAlignmentEndReadFilter) AND HasReadGroupReadFilter) AND MatchingBasesAndQualsReadFilter) AND SeqIsStoredReadFilter)
              2328384 read(s) filtered by: (((ValidAlignmentStartReadFilter AND ValidAlignmentEndReadFilter) AND HasReadGroupReadFilter) AND MatchingBasesAndQualsReadFilter)
                  2328384 read(s) filtered by: ((ValidAlignmentStartReadFilter AND ValidAlignmentEndReadFilter) AND HasReadGroupReadFilter)
                      2328384 read(s) filtered by: HasReadGroupReadFilter 

20:43:58.674 INFO  ProgressMeter -             unmapped              0.1                     0              0.0
20:43:58.674 INFO  ProgressMeter - Traversal complete. Processed 0 total loci in 0.1 minutes.
20:43:58.675 INFO  ASEReadCounter - Shutting down engine
[24 de outubro de 2018 20:43:58 BRST] org.broadinstitute.hellbender.tools.walkers.rnaseq.ASEReadCounter done. Elapsed time: 0.22 minutes.
Runtime.totalMemory()=8367636480

My command line looks like this:

gatk ASEReadCounter -R /path/to/ref.fa \ -I /path/to/sample.bam \ -V /path/to/VCFfile.vcf \ -O output.csv

What could be wrong? I've tried using another vcf file but I still get the same empty output.
Thanks.

During ApplyBQSR, in progressmeter message
i found "unmapped" on Current locus

Does it means 'wrong mapping of these data' ?
or is it OK to analyze of data, ongoing?

If i need to do re-alignment of data or modify methods of previous procedures,
Do you make me know that?

thanks!

Hello, everyone
I'm trying to call snv using mutect2, gatk4.0.9.0 . And the bam was generated from gatk-bqsr.While many sample successfully finished the mutect2, some got ERROR MESSAGE:

INFO Mutect2 - Shutting down engine
[October 24, 2018 12:29:00 PM CST] org.broadinstitute.hellbender.tools.walkers.mutect.Mutect2 done. Elapsed time: 113.02 minutes.
Runtime.totalMemory()=4760535040
** java.lang.NumberFormatException: For input string: "."**
at sun.misc.FloatingDecimal.readJavaFormatString(FloatingDecimal.java:2043)
at sun.misc.FloatingDecimal.parseDouble(FloatingDecimal.java:110)
at java.lang.Double.parseDouble(Double.java:538)
at java.lang.Double.valueOf(Double.java:502)
at htsjdk.variant.variantcontext.CommonInfo.lambda$getAttributeAsDoubleList$2(CommonInfo.java:299)
at java.util.stream.ReferencePipeline$3$1.accept(ReferencePipeline.java:193)
at java.util.Collections$2.tryAdvance(Collections.java:4717)
at java.util.Collections$2.forEachRemaining(Collections.java:4725)
at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:481)
at java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:471)
at java.util.stream.ReduceOps$ReduceOp.evaluateSequential(ReduceOps.java:708)
at java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:234)
at java.util.stream.ReferencePipeline.collect(ReferencePipeline.java:499)
at htsjdk.variant.variantcontext.CommonInfo.getAttributeAsList(CommonInfo.java:273)
at htsjdk.variant.variantcontext.CommonInfo.getAttributeAsDoubleList(CommonInfo.java:293)
at htsjdk.variant.variantcontext.VariantContext.getAttributeAsDoubleList(VariantContext.java:740)
at org.broadinstitute.hellbender.tools.walkers.mutect.GermlineProbabilityCalculator.getGermlineAltAlleleFrequencies(GermlineProbabilityCalculator.java:49)
at org.broadinstitute.hellbender.tools.walkers.mutect.GermlineProbabilityCalculator.getPopulationAFAnnotation(GermlineProbabilityCalculator.java:27)
at org.broadinstitute.hellbender.tools.walkers.mutect.SomaticGenotypingEngine.callMutations(SomaticGenotypingEngine.java:151)
at org.broadinstitute.hellbender.tools.walkers.mutect.Mutect2Engine.callRegion(Mutect2Engine.java:217)
at org.broadinstitute.hellbender.tools.walkers.mutect.Mutect2.apply(Mutect2.java:215)
at org.broadinstitute.hellbender.engine.AssemblyRegionWalker.processReadShard(AssemblyRegionWalker.java:291)
at org.broadinstitute.hellbender.engine.AssemblyRegionWalker.traverse(AssemblyRegionWalker.java:267)
at org.broadinstitute.hellbender.engine.GATKTool.doWork(GATKTool.java:966)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.runTool(CommandLineProgram.java:139)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMainPostParseArgs(CommandLineProgram.java:192)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMain(CommandLineProgram.java:211)
at org.broadinstitute.hellbender.Main.runCommandLineProgram(Main.java:160)
at org.broadinstitute.hellbender.Main.mainEntry(Main.java:203)
at org.broadinstitute.hellbender.Main.main(Main.java:289)

Hi.gatk CombineGVCFs has been running for two days, suddenly interrupted. Whether it（gatk CombineGVCFs） can continue to run on the original basis？
Thank you！

Objective

Apply hard filters to a variant callset that is too small for VQSR or for which truth/training sets are not available.

Caveat

This document is intended to illustrate how to compose and run the commands involved in applying the hard filtering method. The annotations and values used may not reflect the most recent recommendations. Be sure to read the documentation about why you would use hard filters and how to understand and improve upon the generic hard filtering recommendations that we provide.

Steps

1. Extract the SNPs from the call set
2. Determine parameters for filtering SNPs
3. Apply the filter to the SNP call set
4. Extract the Indels from the call set
5. Determine parameters for filtering indels
6. Apply the filter to the Indel call set

1. Extract the SNPs from the call set

Action

Run the following GATK command:

java -jar GenomeAnalysisTK.jar \ 
    -T SelectVariants \ 
    -R reference.fa \ 
    -V raw_variants.vcf \ 
    -selectType SNP \ 
    -o raw_snps.vcf 

Expected Result

This creates a VCF file called raw_snps.vcf, containing just the SNPs from the original file of raw variants.

2. Determine parameters for filtering SNPs

SNPs matching any of these conditions will be considered bad and filtered out, i.e. marked FILTER in the output VCF file. The program will specify which parameter was chiefly responsible for the exclusion of the SNP using the culprit annotation. SNPs that do not match any of these conditions will be considered good and marked PASS in the output VCF file.

• QualByDepth (QD) 2.0

This is the variant confidence (from the QUAL field) divided by the unfiltered depth of non-reference samples.

• FisherStrand (FS) 60.0

Phred-scaled p-value using Fisher’s Exact Test to detect strand bias (the variation being seen on only the forward or only the reverse strand) in the reads. More bias is indicative of false positive calls.

• RMSMappingQuality (MQ) 40.0

This is the Root Mean Square of the mapping quality of the reads across all samples.

• MappingQualityRankSumTest (MQRankSum) -12.5

This is the u-based z-approximation from the Mann-Whitney Rank Sum Test for mapping qualities (reads with ref bases vs. those with the alternate allele). Note that the mapping quality rank sum test can not be calculated for sites without a mixture of reads showing both the reference and alternate alleles, i.e. this will only be applied to heterozygous calls.

• ReadPosRankSumTest (ReadPosRankSum) -8.0

This is the u-based z-approximation from the Mann-Whitney Rank Sum Test for the distance from the end of the read for reads with the alternate allele. If the alternate allele is only seen near the ends of reads, this is indicative of error. Note that the read position rank sum test can not be calculated for sites without a mixture of reads showing both the reference and alternate alleles, i.e. this will only be applied to heterozygous calls.

• StrandOddsRatio (SOR) 3.0

The StrandOddsRatio annotation is one of several methods that aims to evaluate whether there is strand bias in the data. Higher values indicate more strand bias.

3. Apply the filter to the SNP call set

Action

Run the following GATK command:

java -jar GenomeAnalysisTK.jar \ 
    -T VariantFiltration \ 
    -R reference.fa \ 
    -V raw_snps.vcf \ 
    --filterExpression "QD < 2.0 || FS > 60.0 || MQ < 40.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0" \ 
    --filterName "my_snp_filter" \ 
    -o filtered_snps.vcf 

Expected Result

This creates a VCF file called filtered_snps.vcf, containing all the original SNPs from the raw_snps.vcf file, but now the SNPs are annotated with either PASS or FILTER depending on whether or not they passed the filters.

For SNPs that failed the filter, the variant annotation also includes the name of the filter. That way, if you apply several different filters (simultaneously or sequentially), you can keep track of which filter(s) each SNP failed, and later you can retrieve specific subsets of your calls using the SelectVariants tool. To learn more about composing different types of filtering expressions and retrieving subsets of variants using SelectVariants, please see the online GATK documentation.

4. Extract the Indels from the call set

Action

Run the following GATK command:

java -jar GenomeAnalysisTK.jar \ 
    -T SelectVariants \ 
    -R reference.fa \ 
    -V raw_HC_variants.vcf \ 
    -selectType INDEL \ 
    -o raw_indels.vcf 

Expected Result

This creates a VCF file called raw_indels.vcf, containing just the Indels from the original file of raw variants.

5. Determine parameters for filtering Indels.

Indels matching any of these conditions will be considered bad and filtered out, i.e. marked FILTER in the output VCF file. The program will specify which parameter was chiefly responsible for the exclusion of the indel using the culprit annotation. Indels that do not match any of these conditions will be considered good and marked PASS in the output VCF file.

• QualByDepth (QD) 2.0

This is the variant confidence (from the QUAL field) divided by the unfiltered depth of non-reference samples.

• FisherStrand (FS) 200.0

Phred-scaled p-value using Fisher’s Exact Test to detect strand bias (the variation being seen on only the forward or only the reverse strand) in the reads. More bias is indicative of false positive calls.

• ReadPosRankSumTest (ReadPosRankSum) 20.0

This is the u-based z-approximation from the Mann-Whitney Rank Sum Test for the distance from the end of the read for reads with the alternate allele. If the alternate allele is only seen near the ends of reads, this is indicative of error. Note that the read position rank sum test can not be calculated for sites without a mixture of reads showing both the reference and alternate alleles, i.e. this will only be applied to heterozygous calls.

• StrandOddsRatio (SOR) 10.0

The StrandOddsRatio annotation is one of several methods that aims to evaluate whether there is strand bias in the data. Higher values indicate more strand bias.

6. Apply the filter to the Indel call set

Action

Run the following GATK command:

java -jar GenomeAnalysisTK.jar \ 
    -T VariantFiltration \ 
    -R reference.fa \ 
    -V raw_indels.vcf \ 
    --filterExpression "QD < 2.0 || FS > 200.0 || ReadPosRankSum < -20.0" \ 
    --filterName "my_indel_filter" \ 
    -o filtered_indels.vcf 

Expected Result

This creates a VCF file called filtered_indels.vcf, containing all the original Indels from the raw_indels.vcf file, but now the Indels are annotated with either PASS or FILTER depending on whether or not they passed the filters.

For Indels that failed the filter, the variant annotation also includes the name of the filter. That way, if you apply several different filters (simultaneously or sequentially), you can keep track of which filter(s) each Indel failed, and later you can retrieve specific subsets of your calls using the SelectVariants tool. To learn more about composing different types of filtering expressions and retrieving subsets of variants using SelectVariants, please see the online GATK documentation.

I am running a custom made interval_list to count reads in specific intervals in mouse very low pass WGS data (generated from Oxford Nanopore MinION).

I get the output and I can see that the correct reads were filtered from the command line but I can't find them in the tsv file.

Any help would be super appreciated.

Nada

I want to use Mutect2 to subtract out variants present in a wild-type sample from variants present in an organism displaying a desired phenotype. Is Mutect2 appropriate for this? Can I use my wild-type .bam as the normal and the mutant phenotype .bam as the tumor? Do I need to create a PoN for this case? I only have two wild-type .bams
.

Is it planned to add CombineVariants tool into GATK4.0 toolkit (it existed in previous GATK versions)? The only similar tool currently available in GATK4.0 Beta is GatherVCFs which has very limited possibility and cannot concatenate unsorted VCFs or merge different INFO fields correctly.
Thanks!

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recently,i have been studying call snp and indels for RNA-seq all the time.
meanwhile,i read some docs,and i get some conclusion below:
1.it seems that there is not a best-practice workflow for mutiply samples to call snps and indels .
2.maybe i can use the germline variant joint calling workflow to my data , but i need to examine the result carefully.
so i get some questions below:
1.what is the meaning of "Our standard recommendation is to process RNAseq samples individually as laid out in the RNAseq-specific documentation."(this word come from this article)?
2.how can i examine my RNA`s VCF file delivered by the the germline variant joint calling workflow ? use some software ? or just GATK can do this work .
3.and i also wonder which software can visualize my VCF file just like this picture:
(it is cited from this article)
thanks a lot
ps : because my English is so bad , so i cant find another better word to say thanks to GATK team , but i believe you know what kind of meaning i just want to express.

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I have a system installed with ubuntu 18.04.1, Eclipse Photon Release (4.8.0) and Oracle Java 1.8. Java gets crashed whenever I start my eclipse. Then it generates a log file named as hs_err_pid*.log (eg : hs_err_pid4725.log).

Eclipse gets closed as soon as java crashes.

Could you guys please help me to solve this. I suspect this is because of GTK version.

Any idea...?

I am attaching the sample log file with this.