Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • CompBio
    Member
    • Aug 2009
    • 26

    #1

    TopHat Misses Splice Junctions

    I'm currently running a comparison between TopHat and other methods for finding splicing patterns in RNA Seq data. I've got about 250 million 32-nt reads from Arabidopsis. For the genes I am interested in, using other methods I have been able to align reads across many known and novel splice junctions at 100% ID that are unique to these locations (i.e., no multi-hits), with at least 8nt on either side of each junction (anchor regions). However, I am unable to get TopHat to find these junctions.

    These are the TopHat parameters I'm using:

    -g 1 # report only unique hits
    -F 0.01 # report even poorly-represented junctions
    --segment-mismatches=0 # enforce 100% ID for all reads
    --splice-mismatches=0 # enforce 100% ID across junctions
    --min-coverage-intron=10 # minimum allowed intron size for Arabidopsis
    --max-coverage-intron=11000 # maximum intron size found in Arabidopsis
    -i 10 # (as above)
    -I 11000 # (as above)
    --min-segment-intron=10 # (as above)
    --max-segment-intron=11000 # (as above)
    -j TAIR9_GFF3_genes.juncs # pre-processed splice junctions from gene model
    -a 8 # minimum overlap/anchor of 8nt
    -p 4 # allowing up to 4 threads on 8-processor machines

    I can relax the constraint on splice mismatches to see if it helps, but ultimately I would like TopHat to find the junctions at 100% ID that I've already seen using other methods. I would like to make my comparison as fair as possible.

    Any ideas? Am I misinterpreting/misusing any of these parameters?
  • IrisZhu
    Member
    • Jul 2010
    • 25

    #2
    Originally posted by CompBio View Post
    I'm currently running a comparison between TopHat and other methods for finding splicing patterns in RNA Seq data. I've got about 250 million 32-nt reads from Arabidopsis. For the genes I am interested in, using other methods I have been able to align reads across many known and novel splice junctions at 100% ID that are unique to these locations (i.e., no multi-hits), with at least 8nt on either side of each junction (anchor regions). However, I am unable to get TopHat to find these junctions.

    These are the TopHat parameters I'm using:

    -g 1 # report only unique hits
    -F 0.01 # report even poorly-represented junctions
    --segment-mismatches=0 # enforce 100% ID for all reads
    --splice-mismatches=0 # enforce 100% ID across junctions
    --min-coverage-intron=10 # minimum allowed intron size for Arabidopsis
    --max-coverage-intron=11000 # maximum intron size found in Arabidopsis
    -i 10 # (as above)
    -I 11000 # (as above)
    --min-segment-intron=10 # (as above)
    --max-segment-intron=11000 # (as above)
    -j TAIR9_GFF3_genes.juncs # pre-processed splice junctions from gene model
    -a 8 # minimum overlap/anchor of 8nt
    -p 4 # allowing up to 4 threads on 8-processor machines

    I can relax the constraint on splice mismatches to see if it helps, but ultimately I would like TopHat to find the junctions at 100% ID that I've already seen using other methods. I would like to make my comparison as fair as possible.

    Any ideas? Am I misinterpreting/misusing any of these parameters?
    Could the reason be your "-g 1"? Is "1" too small.
    I am always a bit confused about this "-g", coz the default is 40 --- I can't imagine it will keep all the reads that mapped to less than 40 places in the genome.

    Comment

    • anecsulea
      Member
      • Dec 2009
      • 12

      #3
      Hi,

      I don't know very much about Arabidopsis biology, but in mammals there is one class of genes for which TopHat is unable to find the junctions: the genes that generate duplicates through retrotransposition. This is because these duplicate copies are intronless, and thus the reads that
      map on the splice junctions of the parental genes also map perfectly on the genome in the duplicated region. Since TopHat only uses reads that were not mapped on the genome in order to detect junctions, for this class of genes the junctions will not be detected.

      So it might be worth to check if these genes have (recent) retrocopies in Arabidposis.

      Hope this helps !

      Best,

      Anamaria


      Originally posted by CompBio View Post
      I'm currently running a comparison between TopHat and other methods for finding splicing patterns in RNA Seq data. I've got about 250 million 32-nt reads from Arabidopsis. For the genes I am interested in, using other methods I have been able to align reads across many known and novel splice junctions at 100% ID that are unique to these locations (i.e., no multi-hits), with at least 8nt on either side of each junction (anchor regions). However, I am unable to get TopHat to find these junctions.

      Comment

      • CompBio
        Member
        • Aug 2009
        • 26

        #4
        Good suggestion -- relaxing the mismatches requirement may not help much if I don't allow a few multi-reads. I'll apply them both and see what happens.

        Comment

        • john_mu
          Member
          • May 2010
          • 88

          #5
          There is a new program called HMMsplicer that was designed for the Arabidopsis genome. Maybe you can give that a try.

          I haven't personally used it, but they were benchmarking it against SpilceMap and TopHat before.
          SpliceMap: De novo detection of splice junctions from RNA-seq
          Download SpliceMap Comment here

          Comment

          • Lee Sam
            Member
            • Oct 2008
            • 57

            #6
            There is also the consideration that (to my admittedly shallow understanding) TopHat only uses the set of canonical splice signal sequences. Unfortunately, I can't recommend anything better - I was playing with the supersplat aligner which does spliced alignment but the program was very very slow and never ran to completion.

            Comment

            • CompBio
              Member
              • Aug 2009
              • 26

              #7
              Originally posted by Lee Sam View Post
              There is also the consideration that (to my admittedly shallow understanding) TopHat only uses the set of canonical splice signal sequences. Unfortunately, I can't recommend anything better - I was playing with the supersplat aligner which does spliced alignment but the program was very very slow and never ran to completion.
              Actually, that's one of the approaches I'm comparing it to. Supersplat can use a lot of memory that appears to increase with the size of the query file as well as with parameter changes. If you're not careful to split up your files, your machine can spend a lot of time swapping.

              As for TopHat, I'll have to dig into their documentation again to see if I can figure out how it uses the canonical sites. Another good idea -- thanks!

              Comment

              • BAJ
                Member
                • Nov 2008
                • 15

                #8
                Hi,
                I would be interested in how you actually compared the different algorithms?
                You say you used an existing data set... Why don't you use a constructed one? and how do you know what is true or not?
                Could you also please summarize your findings?
                As I am planing to do similar things within the next few weeks I would be of course very interested in any advice you could have.

                Best,
                Bernd

                Comment

                • carmeyeii
                  Senior Member
                  • Mar 2011
                  • 137

                  #9
                  Hi!

                  This is a somewhat old thread, but I would like to know more about the biological constraints TopHat uses to call a splice junction... is there anyway to override this?

                  Comment

                  Latest Articles

                  Collapse

                  • kinpict.com
                    Reply to 16S/ITS Profiling vs. Shotgun Metagenomics: What Changes in Your Workflow?
                    by kinpict.com
                    The part about this topic feels surprisingly grounded, and the details on the page is the bit that made me slow down. I’d keep <a href="https://kinpict.com/">ai family photo generator</a> bookmarked for later.
                    Today, 06:37 PM
                  • SEQadmin2
                    16S/ITS Profiling vs. Shotgun Metagenomics: What Changes in Your Workflow?
                    by SEQadmin2





                    NGS has revolutionized clinical microbiology by offering new ways to identify and surveil pathogens without prior knowledge of the target. One popular approach is 16S rRNA and ITS amplicon sequencing, which targets specific microbial markers. But studies are increasingly incorporating shotgun metagenomics, a technique that sequences all DNA from a sample without targeting specific microbial markers. This approach allows more detailed taxonomic classification,...
                    10-30-2026, 06:46 AM

                  ad_right_rmr

                  Collapse

                  News

                  Collapse

                  Topics Statistics Last Post
                  Started by SEQadmin2, 11-12-2026, 07:59 AM
                  0 responses
                  27 views
                  0 reactions
                  Last Post SEQadmin2  
                  Started by SEQadmin2, 11-05-2026, 09:25 AM
                  0 responses
                  35 views
                  0 reactions
                  Last Post SEQadmin2  
                  Started by SEQadmin2, 11-03-2026, 11:54 AM
                  2 responses
                  56 views
                  0 reactions
                  Last Post kinpict.com  
                  Started by SEQadmin2, 10-28-2026, 09:57 AM
                  0 responses
                  175 views
                  0 reactions
                  Last Post SEQadmin2  
                  Working...