Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • nareshvasani
    Member
    • Apr 2013
    • 57

    #1

    Denovo RNA-Seq assembly using Velvetoptimiser

    Hello Fellows,

    I used velvetoptimiser to find optimal value of Kmer:
    1] I run it from 45 to 71,
    ##VelvetOptimiser.pl -s 45 -e 71 -f '-short -fastq Barcode10_trp1_unmatched_forward_1mismatch_removed-trim300.fastq' -t 8 -k 'n50' -c Lbp

    It ran fine but shows warning like:

    Aug 6 17:45:32 Setting cov_cutoff to 1.483.
    **********
    Warning: Assembly score for assembly_id 14 is 0
    You may want to consider choosing a different optimisation variable or function.
    Current optimisation functions are n50 for k value and Lbp for cov_cutoff
    **********
    Aug 6 17:51:35 Setting cov_cutoff to 0.917.
    **********
    Warning: Assembly score for assembly_id 14 is 0
    You may want to consider choosing a different optimisation variable or function.
    Current optimisation functions are n50 for k value and Lbp for cov_cutoff
    **********
    Looking for best cutoff score between 0.000 and 2.400
    Max cutoff lies between 0.000 & 1.483
    fc = 0 fd = 0 abs diff = 0
    Aug 6 17:52:17 Setting cov_cutoff to 0.567.
    **********
    Warning: Assembly score for assembly_id 14 is 0
    You may want to consider choosing a different optimisation variable or function.
    Current optimisation functions are n50 for k value and Lbp for cov_cutoff
    **********
    Max cutoff lies between 0.000 & 0.917
    fc = 0 fd = 0 abs diff = 0
    Aug 6 17:52:59 Setting cov_cutoff to 0.350.
    **********
    Warning: Assembly score for assembly_id 14 is 0
    You may want to consider choosing a different optimisation variable or function.
    Current optimisation functions are n50 for k value and Lbp for cov_cutoff
    **********
    Optimum value of cutoff is 0.92
    Took 3 iterations
    Aug 6 17:53:41


    Final optimised assembly details:
    ********************************************************
    Assembly id: 14
    Velveth timestamp: Aug 6 2013 17:30:03
    Velvetg timestamp: Aug 6 2013 17:53:39
    Velveth version: 1.2.03
    Velvetg version: 1.2.03
    Readfile(s): -short -fastq Barcode10_trp1_unmatched_forward_1mismatch_removed-trim300.fastq
    Velveth parameter string: auto_data_71 71 -short -fastq Barcode10_trp1_unmatched_forward_1mismatch_removed-trim300.fastq
    Velvetg parameter string: auto_data_71 -clean yes -exp_cov 3 -cov_cutoff 0.3502176
    Assembly directory: /media/DATAPART3/RNA_seq_Analysis_7_26_13/Barcode_Splitter/auto_data_71
    Velvet hash value: 71
    Roadmap file size: 241309783
    Total number of contigs: 13803
    n50: 240
    length of longest contig: 989
    Total bases in contigs: 3215066
    Number of contigs > 1k: 0
    Total bases in contigs > 1k: 0

    ##conclusion it show 71 is optimal

    2] I also run it from 27 to 43, but it show similar kind of warning like above.

    ##conclusion it shows 43 is optimal.

    Can anybody please explain what does this mean?

    Your feedback will be much appreciated!

    Thanks in advance.
  • AdrianP
    Senior Member
    • Apr 2011
    • 130

    #2
    For RNA Seq, dont do such a boad range. Run the assembler from 45 to 55, 57 to 65, 67 to 75. Or split it even in lower intervals. Then, you can merge those assemblies.

    Read the oases manual on how to merge the assemblies.

    Comment

    • nareshvasani
      Member
      • Apr 2013
      • 57

      #3
      Hi Adrian

      But i am just trying find optimal kmer value and n50 value.
      Can you please provide me any better suggetion for fining optimal kmer value.
      How to select best n50 value.

      Thanks.

      Comment

      • AdrianP
        Senior Member
        • Apr 2011
        • 130

        #4
        You are trying to optimize your kmer, for the highest n50, I understand that.

        Many people will agree with me, that optimizing for a higher n50 is wrong, when it comes to genome assemblies.

        You are not even doing a genome assembly, this is RNASeq data. Your goal (or better yet said, my goal if I was doing this), is to have as many mRNA in your contig file as possible, and for them to be as complete as possible.

        n50 has nothing to do with RNA data. It can be computed, but it is meaningless.

        Comment

        • nareshvasani
          Member
          • Apr 2013
          • 57

          #5
          Thanks AdrianP,

          Thanks for your suggestion. It make sense after your explaination. You are right i am not doing genome assembly.
          Then on what basis I should select kmer value? Any suggestion.

          Comment

          • winsettz
            Member
            • Sep 2012
            • 91

            #6
            I would assess coverage of your assembled contigs by your reads (is the coverage good?), and validate against a putative reference database to see if you are assembling noise.

            If you blast your largest unassembled reads, what do you get? Do you get full coverage of all of your reads to it? Or is it bits and pieces mapping to everything in blast?
            Last edited by winsettz; 08-07-2013, 08:31 AM.

            Comment

            • nareshvasani
              Member
              • Apr 2013
              • 57

              #7
              HI winsettz

              Originally posted by winsettz View Post
              I would assess coverage of your assembled contigs by your reads (is the coverage good?), and validate against a putative reference database to see if you are assembling noise.

              If you blast your largest unassembled reads, what do you get? Do you get full coverage of all of your reads to it? Or is it bits and pieces mapping to everything in blast?

              This is first time I am using velvet. I have not done any blast yet.
              I think we need contig.fa file for running blast. I am right?


              Thanks!

              Comment

              • AdrianP
                Senior Member
                • Apr 2011
                • 130

                #8
                Is this Illumina technology that you have sequenced your reads with?

                Comment

                • winsettz
                  Member
                  • Sep 2012
                  • 91

                  #9
                  Originally posted by AdrianP View Post
                  Is this Illumina technology that you have sequenced your reads with?
                  The last thread he posted with mentioned Ion Torrent; but I'm not sure if it's the same libraries.

                  Comment

                  • nareshvasani
                    Member
                    • Apr 2013
                    • 57

                    #10
                    Originally posted by AdrianP View Post
                    Is this Illumina technology that you have sequenced your reads with?
                    It is from ion proton.

                    Comment

                    • nareshvasani
                      Member
                      • Apr 2013
                      • 57

                      #11
                      Originally posted by winsettz View Post
                      The last thread he posted with mentioned Ion Torrent; but I'm not sure if it's the same libraries.
                      It is same libraries.

                      Comment

                      Latest Articles

                      Collapse

                      • SEQadmin2
                        Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
                        by SEQadmin2



                        Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

                        Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
                        ...
                        10-14-2026, 09:55 AM
                      • SEQadmin2
                        New Genomics Technologies Take Aim at Long-Standing Limits
                        by SEQadmin2


                        Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.

                        We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing
                        ...
                        09-28-2026, 10:25 AM

                      ad_right_rmr

                      Collapse

                      News

                      Collapse

                      Topics Statistics Last Post
                      Started by SEQadmin2, 10-15-2026, 10:52 AM
                      0 responses
                      25 views
                      0 reactions
                      Last Post SEQadmin2  
                      Started by SEQadmin2, 10-14-2026, 05:39 AM
                      0 responses
                      31 views
                      0 reactions
                      Last Post SEQadmin2  
                      Started by SEQadmin2, 10-13-2026, 09:56 AM
                      0 responses
                      27 views
                      0 reactions
                      Last Post SEQadmin2  
                      Started by SEQadmin2, 10-09-2026, 11:14 AM
                      0 responses
                      28 views
                      0 reactions
                      Last Post SEQadmin2  
                      Working...