Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • ea11
    Member
    • Jun 2015
    • 36

    Tophat2 high discordant alignments

    Hi,

    I am mapping paired end RNAseq data using tophat2, but the alignment summary generated is showing I am getting a very high discordant alignment rate. The only tophat options I am specifying is -p 16 and -o "DIR". Below is the output from tophat2:


    PHP Code:
    Left reads:
              
    Input     :  88556961
               Mapped   
    :  76938162 (86.9of input)
                
    of these:  20429665 (26.6%) have multiple alignments (622137 have >20)
    Right reads:
              
    Input     :  88556961
               Mapped   
    :  75252663 (85.0of input)
                
    of these:  20114304 (26.7%) have multiple alignments (621700 have >20)
    Unpaired reads:
              
    Input     :     68008
               Mapped   
    :     56927 (83.7of input)
                
    of these:      8045 (14.1%) have multiple alignments (9 have >20)
    85.9overall read mapping rate.

    Aligned pairs:  65389463
         of these
    :  18622479 (28.5%) have multiple alignments
                    61775607 
    (94.5%) are discordant alignments
     4.1
    concordant pair alignment rate
    The flagstat output I get is also below:

    PHP Code:
    341377625 0 in total (QC-passed reads QC-failed reads)
    189129873 0 secondary
    0 supplimentary
    0 duplicates
    341377625 
    0 mapped (100.00%:-nan%)
    152190825 0 paired in sequencing
    76938162 
    0 read1
    75252663 
    0 read2
    263998 
    0 properly paired (0.17%:-nan%)
    130778926 0 with itself and mate mapped
    21411899 
    0 singletons (14.07%:-nan%)
    116104620 0 with mate mapped to a different chr
    80799382 
    0 with mate mapped to a different chr (mapQ>=5

    I am using cutadapt to remove adapters and remove low quality reads and that is running fine. But then when I pass the paired files onto tophat, the results don't seem good. From what I have read, it is to do with the mate pairs no longer being in sync in the two fastq files. Is there a way around this and to get the number of discordant alignments down?

    I have tried aligning the fastq files with tophat2 without passing the files through cutadapt first and the alignment is fine and there is a very low discordant alignment rate, so I'm guessing the fastq files are good, but something is happening after the cutadapt step.
    Just as a note, I am not using Galaxy for the analysis.

    Thanks
  • GenoMax
    Senior Member
    • Feb 2008
    • 7142

    #2
    Originally posted by ea11 View Post
    From what I have read, it is to do with the mate pairs no longer being in sync in the two fastq files. Is there a way around this and to get the number of discordant alignments down?
    Thanks
    Use a paired-end aware trimmer like trimmomatic/BBDuk (from BBMap) which keep the paired end files in sync post trimming.

    That said, if you are happy with the cutadapt results and just want to fix the PE read order you can do so by using repair.sh from BBMap (paired end reads in two files example): http://seqanswers.com/forums/showpos...0&postcount=45

    Comment

    • ea11
      Member
      • Jun 2015
      • 36

      #3
      Thanks for the reply. I though cutadapt did that with the -p option to specify paired end data.
      I shall give BBDuk a try and see the results. I was not happy with the results of trimmomatic on my data, so staying away from that trimmer for now.

      Thanks

      Comment

      • GenoMax
        Senior Member
        • Feb 2008
        • 7142

        #4
        Just checking. You are not switching the R1/R2 files when you use them as input for tophat by mistake? That will produce discordant results for obvious reasons.

        Comment

        • ea11
          Member
          • Jun 2015
          • 36

          #5
          Nope I am not. R1 files are before the R2 files in the script.

          Comment

          • GenoMax
            Senior Member
            • Feb 2008
            • 7142

            #6
            BBMap will do spliced alignments so after you use BBDuk you may want to give BBMap a try on the side while you do your TopHat2 runs.

            Comment

            • ea11
              Member
              • Jun 2015
              • 36

              #7
              Thanks, I shall have a read and see what the results look like with BBDuk/BBMap while my tophat jobs are running

              Comment

              Latest Articles

              Collapse

              • SEQadmin2
                Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
                by SEQadmin2



                Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
                ...
                07-09-2026, 11:10 AM
              • SEQadmin2
                Cancer Drug Resistance: The Lingering Barrier to Rising Survival
                by SEQadmin2



                Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

                There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
                07-08-2026, 05:17 AM
              • GATTACAT
                Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
                by GATTACAT
                Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
                07-01-2026, 11:43 AM

              ad_right_rmr

              Collapse

              News

              Collapse

              Topics Statistics Last Post
              Started by SEQadmin2, 07-13-2026, 10:26 AM
              0 responses
              26 views
              0 reactions
              Last Post SEQadmin2  
              Started by SEQadmin2, 07-09-2026, 10:04 AM
              0 responses
              35 views
              0 reactions
              Last Post SEQadmin2  
              Started by SEQadmin2, 07-08-2026, 10:08 AM
              0 responses
              22 views
              0 reactions
              Last Post SEQadmin2  
              Started by SEQadmin2, 07-07-2026, 11:05 AM
              0 responses
              34 views
              0 reactions
              Last Post SEQadmin2  
              Working...