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  • amango
    Member
    • Dec 2009
    • 17

    #1

    Source of duplication in illumina hiseq paired-end reads?

    I recently received my first short read data set, one lane of 2x100bp Illumina Hiseq reads. I'm hoping the community can help me identify the source of duplicate sequences indicated in fastQC reports on the data.

    FastQC showed high duplication (>60%) for both forward and reverse reads. The report for the reverse reads did not turn up any specific over-represented sequences, while the report for the forward reads identified a PCR primer and adapter sequence. However a bowtie alignment against illumina paired-end adapters and primers showed 0% alignment. And when I tried to use picard to mark and remove duplicate reads, no reads were removed (picard command below).

    My reads are from a single lane of 12 individually barcoded cDNA sub-libraries from a non-model organism (no reference genome). Six of these libraries were normalized (via DSN digestion), six were not. Has anyone seem similar fastQC curves for rna-seq data?

    Is there a way to search the file for the actual sequences that are highly duplicated?

    Full fastQC reports are attached.

    [command run as below, though I have omitted the path for each file]
    nohup java -jar MarkDuplicates.jar INPUT=sequence_file.bam OUTPUT=deduplicated_reads.bam METRICS_FILE=deduplicated_reads_metrics.txt REMOVE_DUPLICATES=true &



    Attached Files
  • arvid
    Senior Member
    • Jul 2011
    • 156

    #2
    I usually see 60-80 % duplication levels in non-normalized RNA-Seq samples. Did you de-multiplex the sequences to see whether there are differences in duplication levels between the normalized and non-normalized libraries? I'd suspect that the normalization didn't work out very well.

    FastQC looks at initial 50-mers for overrepresentation, but as you pointed out yourself, only some adapters were found on the fw strand. You can remove those with e.g. trimmomatic.

    I'm not sure about Picard, but samtools rmdup only works on mapped reads...

    Did you check the rRNA contamination levels already?

    Comment

    • arvid
      Senior Member
      • Jul 2011
      • 156

      #3
      You could run a k-mer counter on the data to check for overrepresentation, e.g. Meryl or Jellyfish...

      Comment

      • simonandrews
        Simon Andrews
        • May 2009
        • 870

        #4
        High duplication levels in RNA-Seq are not necessarily a problem. Duplication simply means that you're getting very high fold coverage. For RNA-Seq it's quite normal to oversequence highly expressed transcripts in order to be able to see lowly expressed transcripts. Duplication warnings are more of a concern when they occur in libraries where you're expecting more equal coverage. 60% also isn't very high - a badly PCR duplicated library might have duplication levels above 90% (our personal record is 98%!). For more details of how to interpret this plot you can look at this blog post.

        Comment

        • harryzs
          Member
          • Dec 2010
          • 30

          #5
          I agree.

          see this http://seqanswers.com/forums/showthr...ght=duplicates

          Originally posted by simonandrews View Post
          High duplication levels in RNA-Seq are not necessarily a problem. Duplication simply means that you're getting very high fold coverage. For RNA-Seq it's quite normal to oversequence highly expressed transcripts in order to be able to see lowly expressed transcripts. Duplication warnings are more of a concern when they occur in libraries where you're expecting more equal coverage. 60% also isn't very high - a badly PCR duplicated library might have duplication levels above 90% (our personal record is 98%!). For more details of how to interpret this plot you can look at this blog post.

          Comment

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