Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Program to relate SNPs to model genome annotation?

    EMS-mutagenesis causes G->A and C->T transitions. In most cases large numbers of these lesions are produced per genome with only one being the source of mutant phenotype screened for.

    I have a lists of 50-100 of these mutations/genome for a number of yeast strains as determined from a SOLiD sequencing run.

    What is the recommended method to convert this information (single base change at a known genomic location) to gene name and effect on the gene (eg, synonymous--no change to protein sequence, 1 residue change to sequence, or truncation)? Seems like something that would already have been written.

    --
    Phillip
    Last edited by pmiguel; 04-13-2010, 07:29 AM. Reason: Typo

  • #2
    Originally posted by pmiguel View Post
    What is the recommended method to convert this information (single base change at a known genomic location) to gene name and effect on the gene (eg, synonymous--no change to protein sequence, 1 residue change to sequence, or truncation)? Seems like something that would already have been written.
    The "consequences" module in our software Nesoni (*) does this... BUT it requires you to use the previous "shrimp" (align) and "consensus" (call) modules beforehand - all the modules share a folder of results. It is mainly useful for bacterial genomes, so perhaps not as useful to you.

    If it is only subsitutions and not indels, it's a pretty simple BioPerl script to take your list and a Genbank file of the genome and test the effects on each CDS.

    (*) Nesoni http://www.vicbioinformatics.com/software.nesoni.shtml

    Comment


    • #3
      Originally posted by Torst View Post
      The "consequences" module in our software Nesoni (*) does this... BUT it requires you to use the previous "shrimp" (align) and "consensus" (call) modules beforehand - all the modules share a folder of results. It is mainly useful for bacterial genomes, so perhaps not as useful to you.

      If it is only subsitutions and not indels, it's a pretty simple BioPerl script to take your list and a Genbank file of the genome and test the effects on each CDS.

      (*) Nesoni http://www.vicbioinformatics.com/software.nesoni.shtml
      Does it handle multiple exon genes okay? I notice you are primarily a bacterial informatics shop...

      Thanks for the response,
      Phillip

      Comment


      • #4
        Originally posted by pmiguel View Post
        Does it handle multiple exon genes okay? I notice you are primarily a bacterial informatics shop...
        Yes as I said we are bacteria focussed. Even in bacteria we have introns sometimes, and pseudo genes are often written as join(a..b,c..d) for the N-term and C-term "exons". Nesoni uses BioPython for the annotation retrieval, so it *may* work. I will talk to the primary author and find out; it probably isn't difficult to alter to work with join() features. You could try it on a small chromosome? (Assuming you have a server with enough RAM)

        --Torst

        Comment


        • #5
          Originally posted by Torst View Post
          Yes as I said we are bacteria focussed. Even in bacteria we have introns sometimes, and pseudo genes are often written as join(a..b,c..d) for the N-term and C-term "exons". Nesoni uses BioPython for the annotation retrieval, so it *may* work. I will talk to the primary author and find out; it probably isn't difficult to alter to work with join() features. You could try it on a small chromosome? (Assuming you have a server with enough RAM)

          --Torst
          Hi Torst,
          Thanks again for you response. I ended up writing a script employing bioperl to do this. Initially I thought it would take me less time than acquiring and installing Nesoni. But since it took me several days to write and debug my code I was probably wrong.
          Phillip

          Comment

          Latest Articles

          Collapse

          • seqadmin
            Essential Discoveries and Tools in Epitranscriptomics
            by seqadmin




            The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist...
            04-22-2024, 07:01 AM
          • seqadmin
            Current Approaches to Protein Sequencing
            by seqadmin


            Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
            04-04-2024, 04:25 PM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by seqadmin, Today, 11:49 AM
          0 responses
          12 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, Yesterday, 08:47 AM
          0 responses
          16 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-11-2024, 12:08 PM
          0 responses
          61 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-10-2024, 10:19 PM
          0 responses
          60 views
          0 likes
          Last Post seqadmin  
          Working...
          X