Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • yarri
    Junior Member
    • Sep 2009
    • 1

    #1

    Assembly using phrap

    Hej!

    I am working on a data my group received from MWG. They were using, as far as I know 454 sequencing to sequence short 3' fragments of cDNA from two populations. My task is to assemble the data and compare the abundance of the transcript.
    I am a beginner, so please excuse me if my questions are silly, here they are:
    1. I have fasta and quality files. I feed them to phrap and I am getting an output - so far so good. Now, how can I obtain information on what was merged into the resulting contigs? I need this information to make comparison of transcript abundance. Phrap provides me with a huge report file but I am not sure how to find this information. Ideally I want to automate the process using python scripts - that is run assembly in phrap and parse the output so I can have a table with a contig sequence and number of reads that were used to create it.
    2. Is this even possible? Should I perhaps use some other tools?
    Thanks in advance.

    Best regards
    Marian Plaszczyca
  • maubp
    Peter (Biopython etc)
    • Jul 2009
    • 1544

    #2
    Since you said you would like to use Python, I'll just point out that Biopython can parse PHRED and ACE files.

    The ACE contig files tell you which reads went into each contig, which sounds like what you want to know.

    Peter

    Comment

    • BENM
      Member
      • May 2009
      • 33

      #3
      Originally posted by yarri View Post
      Hej!

      I am working on a data my group received from MWG. They were using, as far as I know 454 sequencing to sequence short 3' fragments of cDNA from two populations. My task is to assemble the data and compare the abundance of the transcript.
      I am a beginner, so please excuse me if my questions are silly, here they are:
      1. I have fasta and quality files. I feed them to phrap and I am getting an output - so far so good. Now, how can I obtain information on what was merged into the resulting contigs? I need this information to make comparison of transcript abundance. Phrap provides me with a huge report file but I am not sure how to find this information. Ideally I want to automate the process using python scripts - that is run assembly in phrap and parse the output so I can have a table with a contig sequence and number of reads that were used to create it.
      2. Is this even possible? Should I perhaps use some other tools?
      Thanks in advance.

      Best regards
      Marian Plaszczyca
      Hi, Marian
      I have a PERL script here, hope it will help you.
      Command: perl phraplist.pl phrap.out > phrap.list
      Code:
      #!/usr/bin/perl
      #phraplist.pl
      die "Usage:$0 phrap.out\n" if (@ARGV!=1);
      open(PhrapOut, "$ARGV[0]") ||die "could not open $ARGV[0]";
      @line=<PhrapOut>;
      $real=0;
      foreach $hang (@line) {
              if($hang =~/^Contig\s\d+.\s+\d+\s\w+;\s\d+\sbp/ ) {
                      $real=1;
              }
              $real=0 if($hang =~/Contig quality (.*):$/ || $hang =~/^Overall discrep rates/);
      	$real=0 if($hang=~"Overall");
      	print $hang if($real);
      }
      close(PhrapOut);
      The phrap.list contain information as below:

      Code:
      Contig 1.  7 reads; 685 bp (untrimmed), 653 (trimmed).  Isolated contig.
           -1   682 15_A8-9.ab1   604 (  0)  1.55 0.31 0.00   15 ( 58)   23 ( 23) 
            1   679 22_A8-9.ab1   635 (  0)  0.15 0.30 0.15    0 (  6)   23 ( 19) 
            2   673 11_A8-9_R.ab1  580 (  0)  0.67 0.00 0.17   65 ( 65)    6 ( 15) 
            5   686 10_A8-9.ab1   662 (  0)  0.44 0.15 0.00    2 (  2)    1 ( 27) 
            4   684 21_A8-9.ab1   648 (  0)  0.59 0.15 0.15    7 (  7)    1 ( 24) 
      C   139   522 A8-9.ref.scf  381 (  0)  0.00 0.00 0.00    0 (  0)    0 (  0) 
      C   352   641 23_A8-9.ab1   120 (  0)  0.00 0.00 0.79  147 (147)   16 ( 16)

      Comment

      Latest Articles

      Collapse

      • SEQadmin2
        Beyond CRISPR/Cas9: Understand, Choose, and Use the Right Genome Editing Tool
        by SEQadmin2



        CRISPR/Cas9 sparked the gene editing revolution for both research and therapeutics.1 But this system still showed severe issues that limited its applications. The most prominent were the heavy reliance on PAM sequences, delivery limitations, double-stranded breaks that prompt unintended edits and cell death, and editing inefficiency (both in targeting and in knock-in reliability).

        Despite this, “CRISPR helped turn genome editing from a specialized technique into
        ...
        07-31-2026, 11:01 AM
      • SEQadmin2
        Proteomic Platforms: How to Choose the Right Analytical Strategy to Improve Detection and Clinical Applications
        by SEQadmin2


        Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.

        The systematic characterization of the human proteome has
        ...
        07-20-2026, 11:48 AM

      ad_right_rmr

      Collapse

      News

      Collapse

      Topics Statistics Last Post
      Started by SEQadmin2, 08-06-2026, 07:41 AM
      0 responses
      14 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 08-03-2026, 10:13 AM
      0 responses
      31 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 07-31-2026, 02:55 AM
      0 responses
      40 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 07-24-2026, 12:17 PM
      0 responses
      26 views
      0 reactions
      Last Post SEQadmin2  
      Working...