htsjdk.tribble.TribbleException: The provided VCF file is malformed at approximately line number 253941: unparsable vcf record with allele -

GitHub | ooliynyk | 6 months ago
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  1. 0

    vcf2adam unparsable vcf record

    GitHub | 6 months ago | ooliynyk
    htsjdk.tribble.TribbleException: The provided VCF file is malformed at approximately line number 253941: unparsable vcf record with allele -
  2. 0

    Investigate failures to load ExAC.0.3.GRCh38.vcf variants

    GitHub | 1 month ago | heuermh
    htsjdk.tribble.TribbleException: The provided VCF file is malformed at approximately line number 15364: Duplicate allele added to VariantContext: C
  3. 0

    GitHub comment 1114#252664902

    GitHub | 4 months ago | heuermh
    java.util.concurrent.ExecutionException: htsjdk.tribble.TribbleException: The provided VCF file is malformed at approximately line number 21: The VCF specification requires a valid filter status: filter was
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    Root Cause Analysis

    1. htsjdk.tribble.TribbleException

      The provided VCF file is malformed at approximately line number 253941: unparsable vcf record with allele -

      at htsjdk.variant.vcf.AbstractVCFCodec.generateException()
    2. HTS JDK
      AbstractVCFCodec.decode
      1. htsjdk.variant.vcf.AbstractVCFCodec.generateException(AbstractVCFCodec.java:783)
      2. htsjdk.variant.vcf.AbstractVCFCodec.checkAllele(AbstractVCFCodec.java:569)
      3. htsjdk.variant.vcf.AbstractVCFCodec.parseAlleles(AbstractVCFCodec.java:531)
      4. htsjdk.variant.vcf.AbstractVCFCodec.parseVCFLine(AbstractVCFCodec.java:336)
      5. htsjdk.variant.vcf.AbstractVCFCodec.decodeLine(AbstractVCFCodec.java:279)
      6. htsjdk.variant.vcf.AbstractVCFCodec.decode(AbstractVCFCodec.java:257)
      6 frames
    3. org.seqdoop.hadoop_bam
      VCFRecordReader.nextKeyValue
      1. org.seqdoop.hadoop_bam.VCFRecordReader.nextKeyValue(VCFRecordReader.java:144)
      1 frame
    4. Spark
      InterruptibleIterator.hasNext
      1. org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:163)
      2. org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
      2 frames
    5. Scala
      Iterator$$anon$11.hasNext
      1. scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
      2. scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
      3. scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
      3 frames
    6. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12$$anonfun$apply$4.apply$mcV$sp(PairRDDFunctions.scala:1034)
      2. org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12$$anonfun$apply$4.apply(PairRDDFunctions.scala:1034)
      3. org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12$$anonfun$apply$4.apply(PairRDDFunctions.scala:1034)
      4. org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1206)
      5. org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1042)
      6. org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1014)
      7. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
      8. org.apache.spark.scheduler.Task.run(Task.scala:88)
      9. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
      9 frames
    7. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
      3. java.lang.Thread.run(Thread.java:745)
      3 frames