Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • Tsuyoshi
    Member
    • Sep 2012
    • 24

    #1

    Reciproca blast using Python

    HI
    I am running local Blast (version 2.2.6) on a mac machine, and I want to find the homologs between two protein database(named A and B) by reciprocal blast methods under python command lines.
    I have succeeded in blast A against B, and B against A, which resulted in two csv files which contained the best hits from each blast. Next I would like to use these two files to do Reciprocal blast, namely to find the homologs between A and B, according to the blast e-value and bit scores.

    The codes for reciprocal blast was downloaded from http://ged.msu.edu/angus/tutorials/r...cal-blast.html
    and it is like this
    ******************************************************************************************************

    #! /usr/bin/env python
    import sys, csv

    # number below which to discard results
    E_CUTOFF = 1e-3

    def load_csv_to_dict(filename):
    """
    Load the CSV file into a dictionary, tying query sequences to subject
    sequences.
    """
    d = {}

    for (query_name, subject_name, score,expect) in csv.reader(open(filename)):
    # fix the names that start with a 'gi|XXXXXXX|'
    query_name = demangle_name(query_name)
    subject_name = demangle_name(subject_name)

    # convert the e-value into a floating point number
    expect = float(expect)
    if query_name not in d and expect < E_CUTOFF:
    # if we don't already have an entry for this, put it in.
    d[query_name] = subject_name

    return d

    def demangle_name(name):
    """
    This functions strips off the 'gi|XXXXX|' name encoding that NCBI uses.

    Note that NCBI does this automatically for subject sequences.
    """
    if name.startswith('gi|'):
    name = name.split('|')
    name = name[2:]
    name = "|".join(name)

    return name

    ###

    # This is the code that's run when you actually type 'find-reciprocal.py'
    # at the command line; the above are function definitions, that define
    # reusable blocks or chunks of code.

    in_file_1 = sys.argv[1]
    in_file_2 = sys.argv[2]

    d1 = load_csv_to_dict(in_file_1)
    d2 = load_csv_to_dict(in_file_2)

    output = csv.writer(sys.stdout)

    for seqname in d1:
    seqmatch1 = d1[seqname]
    seqmatch2 = d2.get(seqmatch1)

    if seqmatch2 == seqname:
    output.writerow([seqname, seqmatch1])

    *******************************************************************************************************
    However, when I used this command, an error came up like

    *******************************************************************************************************

    Traceback (most recent call last):
    File "ngs-course/blast/find-reciprocal.py", line 49, in <module>
    d1 = load_csv_to_dict(in_file_1)
    File "ngs-course/blast/find-reciprocal.py", line 14, in load_csv_to_dict
    for (query_name, subject_name, score,expect) in csv.reader(open(filename)):
    _csv.Error: new-line character seen in unquoted field - do you need to open the file in universal-newline mode?

    *******************************************************************************************************

    Would anyone please help me to modify the command lines to analyse the data? It would be a great appreciation for discussion here. Thanks!
    3
    Always
    66.67%
    2
    Sometimes
    33.33%
    1
    Never
    0.00%
    0

    The poll is expired.

    Last edited by Tsuyoshi; 09-07-2012, 03:53 AM.
  • dariober
    Senior Member
    • May 2010
    • 311

    #2
    Hello,

    I don't have a file to test this but looking at the Pyhton documentation for open() (http://docs.python.org/library/functions.html#open) and at this post found by Google (http://selfsolved.com/problems/pytho...l-newline-mode), you might fix your problem by replacing csv.reader(open(filename)) with csv.reader(open(filename, "rU")) in function load_csv_to_dict(filename). That is, the new function would be:

    Code:
    def load_csv_to_dict(filename):
        """
        Load the CSV file into a dictionary, tying query sequences to subject
        sequences.
        """
        d = {}
    
        for (query_name, subject_name, score,expect) in csv.reader(open(filename, "rU")):
            # fix the names that start with a 'gi|XXXXXXX|'
            query_name = demangle_name(query_name)
            subject_name = demangle_name(subject_name)
    
            # convert the e-value into a floating point number
            expect = float(expect)
            if query_name not in d and expect < E_CUTOFF:
                # if we don't already have an entry for this, put it in.
                d[query_name] = subject_name
    
        return d
    Post a sample file to reproduce the error would help if you can.

    Best
    Dario

    Comment

    • Tsuyoshi
      Member
      • Sep 2012
      • 24

      #3
      Dear Dario,
      Thank you for your kind answer!
      Now it works well!
      Thanks!

      Comment

      • Tsuyoshi
        Member
        • Sep 2012
        • 24

        #4
        Dear Dario,
        Thank you so much!
        It works!

        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, Yesterday, 11:13 AM
        0 responses
        16 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, Yesterday, 10:48 AM
        0 responses
        17 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 10-15-2026, 10:52 AM
        0 responses
        35 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 10-14-2026, 05:39 AM
        0 responses
        42 views
        0 reactions
        Last Post SEQadmin2  
        Working...