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  • Trimming limitation

    Hi dear all

    I have two questions:

    1. In my fastqc output, there is a failure in "Per base sequence content". The problem is for first nine base pairs. I know the irregularity in first 9 positions is not due to adapters contamination. Am I allowed to trim these first 9 base pair ?

    2. How much I can trim a sequence? I know I can trim a sequence as much as I want. but output of my analysis won't be reliable if I trim almost half of the base pairs. Am I right? So I mean how much I can trim my sequences without affecting final result (The goal) of my analysis?

  • #2
    Hi Saeideh,

    1. you can always trim spurious 5' region.
    2. Using TopHat2, you'll get a warning, if you have reads smaller than 20 bp. I usually use this threshold as a lower limit. It is always a trade-off between total mapping rate (more trimming) and uniquely mappings (longer reads).

    The Library-Prep-Kit, the data originated from, should have a small section about handling of reads. Especially in case of 9 bp 5' adapter (maybe random-primer) contamination.

    Comment


    • #3
      Is this an RNAseq dataset? If so, don't trim it. Actually, unless you know why it's there and whether that's a problem then it's best not to trim it off.

      Trim adapters. Whether to trim low quality bases or not is determined by what you need to do. Aside from that, one shouldn't do further trimming without a good reason.

      Comment


      • #4
        Originally posted by dpryan View Post
        Is this an RNAseq dataset? If so, don't trim it. Actually, unless you know why it's there and whether that's a problem then it's best not to trim it off.

        Trim adapters. Whether to trim low quality bases or not is determined by what you need to do. Aside from that, one shouldn't do further trimming without a good reason.

        (1) How about reads length <20bp , I have trimmed them. Does it impact results too much? I thought your suggestion is better to leave them.

        (2) And besides general adapter, if fastqc shows overrepresented sequence 's possible source = TrueSeq index Adapters, Does it mean I need trim corresponding index Adapters as well or still leave it?

        Thank you!
        Last edited by super0925; 03-17-2016, 10:19 AM.

        Comment


        • #5
          Super-short reads are uninformative. Unless you are doing something special like small-non-coding RNA sequencing (where you expect sequences <20bp) those reads are not very useful.

          As Devon said, adapter-trimming is useful. You have not stated how you are trimming things. What are you doing?

          As for "general adapter" - well, there are no "general" adapters, only specific adapters. If you did adapter-trimming and FastQC identifies TrueSeq adapters in your results, you did it wrong. Furthermore, even though I encourage people to trim for all known common adapters, it's strictly better to trim only the adapters that are actually present, when you know their identity. I don't typically recommend that because in practice people downstream don't usually know which specific adapters were used, and including additional adapters for trimming does not cause problems if you have reasonable specificity. But if you do know, absolutely, exactly which adapters (including index sequence) were used, then using only those as a reference is by far the best approach.

          Comment


          • #6
            Originally posted by Brian Bushnell View Post
            Super-short reads are uninformative. Unless you are doing something special like small-non-coding RNA sequencing (where you expect sequences <20bp) those reads are not very useful.

            As Devon said, adapter-trimming is useful. You have not stated how you are trimming things. What are you doing?

            As for "general adapter" - well, there are no "general" adapters, only specific adapters. If you did adapter-trimming and FastQC identifies TrueSeq adapters in your results, you did it wrong. Furthermore, even though I encourage people to trim for all known common adapters, it's strictly better to trim only the adapters that are actually present, when you know their identity. I don't typically recommend that because in practice people downstream don't usually know which specific adapters were used, and including additional adapters for trimming does not cause problems if you have reasonable specificity. But if you do know, absolutely, exactly which adapters (including index sequence) were used, then using only those as a reference is by far the best approach.
            Hi Brian
            Thank you so much!
            1. I always keep reads>20bp in Illumina. I am doing mRNA-Seq.
            But do you mean if ncRNA, I need to keep <20bp if the Quality score >28.
            2. The staff who do the sequencing told me the adapters have been removed when he did sequencing. But I still insist to use cutadapter to remove the TruSeq Universal Adapter for every samples. and meanwhile, I'd like to remove TruSeq Index Adapters(1-27) if it found by FASTQC 'overrepresented seqeunce'.
            Is that OK?

            Comment

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