Hi,
in the BestPractice workflows you advise to use HaplotypeCaller with the "-XX:GCTimeLimit=50" and "-X:GCHeapFreeLimit=10" java options.
Is there something similar for CNNScoreVariants? I tried to use several java options with different values to limit threads but it is quite impossible. Without any option I have 116 threads, running only one command, with 5 java options I can limit them to 95 ... still too much! What should I limit here?
Many thanks
Hi, is there a way to know how many plus or minus strands are removed by HaplotypeCaller when comparing its AD with track numbers in IGV? I can see only in caller output QUAL, GQ, QD, AD, DP, PL, MQ, FS etc. Would like to know for maximum concordance with Sanger.
Thanks a lot, any help appreciated -Anne
One usage example is to refine genotypes based on the discovered allele frequency in an input VCF containing many samples
gatk --java-options "-Xmx4g" CalculateGenotypePosteriors \
-V multisample_input.vcf.gz \
-O output.vcf.gz
Now if I have a case-control cohort of autoimmune disease, I wonder if I should run the above step separately for case and control, or put them into one vcf file?
Thanks for any insight!
Hi,
I am trying to test the pathseq tutorial following the tutorial on this link
I ran the following commands
bioinfo@bioinfo$ conda activate gatk
(gatk) bioinfo@bioinfo$ gatk PathSeqPipelineSpark \
> --input test_sample.bam \
> --filter-bwa-image hg19mini.fasta.img \
> --kmer-file hg19mini.hss \
> --min-clipped-read-length 70 \
> --microbe-fasta e_coli_k12.fasta \
> --microbe-bwa-image e_coli_k12.fasta.img \
> --taxonomy-file e_coli_k12.db \
> --output output.pathseq.bam \
> --scores-output output.pathseq.txt
And encountered below error:
Using GATK jar /home/bioinfo/Installers/gatk4/gatk-4.1.0.0/gatk-package-4.1.0.0-local.jar
Running:
java -Dsamjdk.use_async_io_read_samtools=false -Dsamjdk.use_async_io_write_samtools=true -Dsamjdk.use_async_io_write_tribble=false -Dsamjdk.compression_level=2 -jar /home/bioinfo/Installers/gatk4/gatk-4.1.0.0/gatk-package-4.1.0.0-local.jar PathSeqPipelineSpark --input test_sample.bam --filter-bwa-image hg19mini.fasta.img --kmer-file hg19mini.hss --min-clipped-read-length 70 --microbe-fasta e_coli_k12.fasta --microbe-bwa-image e_coli_k12.fasta.img --taxonomy-file e_coli_k12.db --output output.pathseq.bam --scores-output output.pathseq.txt
18:57:39.629 WARN SparkContextFactory - Environment variables HELLBENDER_TEST_PROJECT and HELLBENDER_JSON_SERVICE_ACCOUNT_KEY must be set or the GCS hadoop connector will not be configured properly
18:57:39.729 INFO NativeLibraryLoader - Loading libgkl_compression.so from jar:file:/home/bioinfo/Installers/gatk4/gatk-4.1.0.0/gatk-package-4.1.0.0-local.jar!/com/intel/gkl/native/libgkl_compression.so
18:57:41.594 INFO PathSeqPipelineSpark - ------------------------------------------------------------
18:57:41.594 INFO PathSeqPipelineSpark - The Genome Analysis Toolkit (GATK) v4.1.0.0
18:57:41.594 INFO PathSeqPipelineSpark - For support and documentation go to https://software.broadinstitute.org/gatk/
18:57:41.739 INFO PathSeqPipelineSpark - Initializing engine
18:57:41.739 INFO PathSeqPipelineSpark - Done initializing engine
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
19/03/05 18:57:41 INFO SparkContext: Running Spark version 2.2.0
18:57:41.968 WARN NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18:57:42.155 INFO PathSeqPipelineSpark - Shutting down engine
[5 March, 2019 6:57:42 PM IST] org.broadinstitute.hellbender.tools.spark.pathseq.PathSeqPipelineSpark done. Elapsed time: 0.04 minutes.
Runtime.totalMemory()=645922816
Exception in thread "main" java.lang.ExceptionInInitializerError
at org.apache.spark.SparkConf.validateSettings(SparkConf.scala:546)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:373)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at org.broadinstitute.hellbender.engine.spark.SparkContextFactory.createSparkContext(SparkContextFactory.java:178)
at org.broadinstitute.hellbender.engine.spark.SparkContextFactory.getSparkContext(SparkContextFactory.java:110)
at org.broadinstitute.hellbender.engine.spark.SparkCommandLineProgram.doWork(SparkCommandLineProgram.java:28)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.runTool(CommandLineProgram.java:138)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMainPostParseArgs(CommandLineProgram.java:191)
at org.broadinstitute.hellbender.cmdline.CommandLineProgram.instanceMain(CommandLineProgram.java:210)
at org.broadinstitute.hellbender.Main.runCommandLineProgram(Main.java:162)
at org.broadinstitute.hellbender.Main.mainEntry(Main.java:205)
at org.broadinstitute.hellbender.Main.main(Main.java:291)
Caused by: java.net.UnknownHostException: bioinfo: bioinfo: unknown error
at java.net.InetAddress.getLocalHost(InetAddress.java:1505)
at org.apache.spark.util.Utils$.findLocalInetAddress(Utils.scala:891)
at org.apache.spark.util.Utils$.org$apache$spark$util$Utils$$localIpAddress$lzycompute(Utils.scala:884)
at org.apache.spark.util.Utils$.org$apache$spark$util$Utils$$localIpAddress(Utils.scala:884)
at org.apache.spark.util.Utils$$anonfun$localHostName$1.apply(Utils.scala:941)
at org.apache.spark.util.Utils$$anonfun$localHostName$1.apply(Utils.scala:941)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.localHostName(Utils.scala:941)
at org.apache.spark.internal.config.package$.<init>(package.scala:204)
at org.apache.spark.internal.config.package$.<clinit>(package.scala)
... 12 more
Caused by: java.net.UnknownHostException: bioinfo: unknown error
at java.net.Inet6AddressImpl.lookupAllHostAddr(Native Method)
at java.net.InetAddress$2.lookupAllHostAddr(InetAddress.java:928)
at java.net.InetAddress.getAddressesFromNameService(InetAddress.java:1323)
at java.net.InetAddress.getLocalHost(InetAddress.java:1500)
... 21 more
I'm in a situation to make variant calls from a mouse tumor cell line. We have RNA-Seq data from this tumor cell line but for the matched normal, what we have is the whole exome sequencing data. Is there any tools/workflows I can use in this case? Thanks!