Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • De novo trouble

    Hello,

    I have 1.3 million paired-end 454 reads for a bacterial genome with an expected size of 4.5 MB.

    When I tried de novo assembly using the default Newbler parameters it estimated a genome size of 197 MB!! I got over 2000 contigs with an N50 of 2216 bases

    Is there an input parameter for expected genome size? Or are there any other parameters that I should modify to get a better output?

    Thanks,
    Swapna

  • #2
    Take it to your support rep. Newbler's genome size estimate are calculated directly from the coverage depth histogram immediately preceding it in the 454NewblerMetrics.txt file. So if that histogram is skewed for some reason the size estimate will be off. 2000 contigs for a 4.5 Mb genome is very bad, therefore you probably have something about your experiment that is causing it to contig poorly. The first thing that springs to mind is that your 1.3 million reads seems like way more than you really need. If they are 400 bp each and they all derive from your genome of interest, that's something like 115x. Newbler likes 20-35x the best, so try assembling less data. Second, if you have contaminants from other genomes then you could really be looking at a combination of contigs from your genome of interest, plus a whole lot of garbage from the contamination. The total contig length might give you a clue about this, as would the size distribution and coverage distribution of contigs (check 454ContigGraph.txt). Finally if the genome is highly repetitive or extremely biased in AT content (like P.falciparum, which is somethiing like 80% AT) then it might be really hard to get good contigging no matter what you do. Do any of these scenarios seem likely to you?

    Comment

    Latest Articles

    Collapse

    • seqadmin
      Best Practices for Single-Cell Sequencing Analysis
      by seqadmin



      While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
      Today, 07:15 AM
    • seqadmin
      Latest Developments in Precision Medicine
      by seqadmin



      Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

      Somatic Genomics
      “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
      05-24-2024, 01:16 PM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by seqadmin, Today, 08:18 AM
    0 responses
    8 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, Today, 08:04 AM
    0 responses
    10 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 06-03-2024, 06:55 AM
    0 responses
    13 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 05-30-2024, 03:16 PM
    0 responses
    27 views
    0 likes
    Last Post seqadmin  
    Working...
    X