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/tools/ilmn_pacbio/assembly_stats.py

https://bitbucket.org/cistrome/cistrome-harvard/
Python | 83 lines | 62 code | 3 blank | 18 comment | 13 complexity | 2af778b1cc55a62e94a7a05b62f39c04 MD5 | raw file
 1#!/usr/bin/env python
 2#
 3#Copyright (c) 2011, Pacific Biosciences of California, Inc.
 4#
 5#All rights reserved.
 6#
 7#Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
 8#    * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
 9#    * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
10#    * Neither the name of Pacific Biosciences nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
11#
12#THIS SOFTWARE IS PROVIDED BY PACIFIC BIOSCIENCES AND ITS CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
13#WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL PACIFIC BIOSCIENCES OR ITS CONTRIBUTORS BE LIABLE FOR ANY
14#DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
15#LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
16#(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
17#
18import sys, os
19from optparse import OptionParser
20from galaxy import eggs
21import pkg_resources
22pkg_resources.require( 'bx-python' )
23from bx.seq.fasta import FastaReader
24
25def getStats( fastaFile, genomeLength, minContigLength ):
26    lengths = []
27    stats = { "Num" : 0,
28              "Sum" : 0, 
29              "Max" : 0, 
30              "Avg" : 0,
31              "N50" : 0,
32              "99%" : 0 }
33    fasta_reader = FastaReader( open( fastaFile, 'rb' ) )
34    while True:
35        seq = fasta_reader.next()
36        if not seq:
37            break
38        if seq.length < minContigLength:
39            continue
40        lengths.append( seq.length )
41    if lengths:
42        stats[ 'Num' ] = len( lengths )
43        stats[ 'Sum' ] = sum( lengths )
44        stats[ 'Max' ] = max( lengths )
45        stats[ 'Avg' ] = int( sum( lengths ) / float( len( lengths ) ) )
46        stats[ 'N50' ] = 0
47        stats[ '99%' ] = 0
48        if genomeLength == 0:
49            genomeLength = sum( lengths )
50        lengths.sort()
51        lengths.reverse()
52        lenSum = 0
53        stats[ "99%" ] = len( lengths )
54        for idx, length in enumerate( lengths ):
55            lenSum += length
56            if ( lenSum > genomeLength / 2 ):
57                stats[ "N50" ] = length
58                break
59        lenSum = 0
60        for idx, length in enumerate( lengths ):
61            lenSum += length
62            if lenSum > genomeLength * 0.99:
63                stats[ "99%" ] = idx + 1
64                break
65    return stats
66
67def __main__():
68    #Parse Command Line
69    usage = 'Usage: %prog input output --minContigLength'
70    parser = OptionParser( usage=usage )
71    parser.add_option( "--minContigLength", dest="minContigLength", help="Minimum length of contigs to analyze" )
72    parser.add_option( "--genomeLength", dest="genomeLength", help="Length of genome for which to calculate N50s" )
73    parser.set_defaults( minContigLength=0, genomeLength=0 )
74    options, args = parser.parse_args()
75    input_fasta_file = args[ 0 ]
76    output_tabular_file = args[ 1 ]
77    statKeys = "Num Sum Max Avg N50 99%".split( " " )
78    stats = getStats( input_fasta_file, int( options.genomeLength ), int( options.minContigLength ) )
79    fout = open( output_tabular_file, "w" )
80    fout.write( "%s\n" % "\t".join( map( lambda key: str( stats[ key ] ), statKeys ) ) )
81    fout.close()
82
83if __name__=="__main__": __main__()