Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • jeffgao
    Junior Member
    • Jun 2011
    • 7

    #1

    unreproducible velvetg results?

    Hello,

    When I generated a Roadmaps and a Sequences by velveth, and applied multiple times of velvetg on them, I found the results were not consistent. The resulted node number, n50 length, max length, total length, and used reads would always be greatly different each rime I ran velvetg.

    I am sure I used the same Roadmaps and Sequences files for each velvetg run, and I deleted LastGraph, stats.txt, contigs.fa, Graph2, and PreGraph files but only kept Roadmaps and Sequences files before I ran velvetg.

    I always used the same velvetg command line as the following,
    ./velvetg results -exp_cov 8 -cov_cutoff 4

    But I always saw different results showing up after the assembly: e.g., n50 length varies from 300k to 500k.

    More details:
    - The velvet version is 1.1.04;
    - My system is ubuntu 11.04;
    - I used the MP (shortjump) data as described in http://gage.cbcb.umd.edu/data/Staphy...aureus/README;
    - I used reverse complement reads and shuffled them into a single file.
    - I used "./velveth results 23 -fastq -shortPaired data/shortjump_shuffled.fastq" to generate Roadmaps and Sequences files.
    - I used "./velvetg results -exp_cov 8 -cov_cutoff 4" for assembly.

    Would anyone give me some hints that what was going on? Thanks a lot!

    Best,
    Jeff
  • jeffgao
    Junior Member
    • Jun 2011
    • 7

    #2
    Am I lucky to get some quick replies? such as whether your velvetg results are reproducible (yes or no) and your guess if your answer is "no". Thanks again!

    Comment

    • aloliveira
      Member
      • Aug 2010
      • 47

      #3
      ooh,

      I constantly use the velvet and every day I deal with this problem, I do not know where the is the problem, to be honest. I never found any documentation or information as to why this occurs. But I think any kind of help or comments would be welcome.

      Comment

      • jeffgao
        Junior Member
        • Jun 2011
        • 7

        #4
        aloliveira,

        Here is the answer I got from velvet's author Daniel Zerbino:

        this is probably linked to the fact that you are using OpenMP.

        The number of reads used is extremely stable (coefficient of variation 6e-5 !) as well as the total length (3e-2). I suspect the large jumps in N50 are mainly due to the fact that the number of contigs rather small (~5200, of which probably many tiny ones) so at this level of granularity, there are only a handful of big gaps which are being bridged. If for random reasons a gap is bridged or not, this is enough to multiply the max contig length by a factor of 2, and the N50 is notoriously unstable on small sets (it behaves essentially like a median).
        If you remove the "OPENMP=1" while compiling velvet, the output will be consistent. I have tested this. Anyway, looking at N50 alone will be confusing if there are lots of small contigs existing.

        - Jeff

        Comment

        • aloliveira
          Member
          • Aug 2010
          • 47

          #5
          Thank you very much jeff.

          Comment

          • rahularjun86
            Member
            • Jan 2011
            • 58

            #6
            Dear all,
            Can we use same Sequence and Roadmap files generated from velveth by "OPENMP=1" for different cov_cutoff (2 to 15)? Or I need to rerun velveth for different cov_cutoff ??
            Many thanks,
            Rahul
            Rahul Sharma,
            Ph.D
            Frankfurt am Main, Germany

            Comment

            Latest Articles

            Collapse

            • 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, detection...
              Today, 06:46 AM
            • 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

            ad_right_rmr

            Collapse

            News

            Collapse

            Topics Statistics Last Post
            Started by SEQadmin2, 10-28-2026, 09:57 AM
            0 responses
            23 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 10-28-2026, 09:51 AM
            0 responses
            15 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 10-22-2026, 11:13 AM
            0 responses
            68 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 10-22-2026, 10:48 AM
            0 responses
            48 views
            0 reactions
            Last Post SEQadmin2  
            Working...