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annotate flanking_features.py @ 1:850c05b9af00 draft
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author | devteam |
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date | Tue, 13 Oct 2015 12:50:14 -0400 |
parents | e928e029f6eb |
children | 94248d5b9b8b |
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0 | 1 #!/usr/bin/env python |
2 #By: Guruprasad Ananda | |
3 """ | |
4 Fetch closest up/downstream interval from features corresponding to every interval in primary | |
5 | |
6 usage: %prog primary_file features_file out_file direction | |
7 -1, --cols1=N,N,N,N: Columns for start, end, strand in first file | |
8 -2, --cols2=N,N,N,N: Columns for start, end, strand in second file | |
9 -G, --gff1: input 1 is GFF format, meaning start and end coordinates are 1-based, closed interval | |
10 -H, --gff2: input 2 is GFF format, meaning start and end coordinates are 1-based, closed interval | |
11 """ | |
12 | |
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13 import fileinput |
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14 import sys |
0 | 15 from bx.cookbook import doc_optparse |
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16 from bx.intervals.io import Comment, GenomicInterval, Header, NiceReaderWrapper |
0 | 17 from bx.intervals.operations import quicksect |
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18 from bx.tabular.io import ParseError |
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19 from galaxy.tools.util.galaxyops import fail, parse_cols_arg, skipped |
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20 from utils.gff_util import convert_bed_coords_to_gff, GFFIntervalToBEDReaderWrapper |
0 | 21 |
22 assert sys.version_info[:2] >= ( 2, 4 ) | |
23 | |
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24 |
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25 def get_closest_feature(node, direction, threshold_up, threshold_down, report_func_up, report_func_down): |
0 | 26 #direction=1 for +ve strand upstream and -ve strand downstream cases; and it is 0 for +ve strand downstream and -ve strand upstream cases |
27 #threhold_Up is equal to the interval start for +ve strand, and interval end for -ve strand | |
28 #threhold_down is equal to the interval end for +ve strand, and interval start for -ve strand | |
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29 if direction == 1: |
0 | 30 if node.maxend <= threshold_up: |
31 if node.end == node.maxend: | |
32 report_func_up(node) | |
33 elif node.right and node.left: | |
34 if node.right.maxend == node.maxend: | |
35 get_closest_feature(node.right, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
36 elif node.left.maxend == node.maxend: | |
37 get_closest_feature(node.left, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
38 elif node.right and node.right.maxend == node.maxend: | |
39 get_closest_feature(node.right, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
40 elif node.left and node.left.maxend == node.maxend: | |
41 get_closest_feature(node.left, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
42 elif node.minend <= threshold_up: | |
43 if node.end <= threshold_up: | |
44 report_func_up(node) | |
45 if node.left and node.right: | |
46 if node.right.minend <= threshold_up: | |
47 get_closest_feature(node.right, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
48 if node.left.minend <= threshold_up: | |
49 get_closest_feature(node.left, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
50 elif node.left: | |
51 if node.left.minend <= threshold_up: | |
52 get_closest_feature(node.left, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
53 elif node.right: | |
54 if node.right.minend <= threshold_up: | |
55 get_closest_feature(node.right, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
56 elif direction == 0: | |
57 if node.start > threshold_down: | |
58 report_func_down(node) | |
59 if node.left: | |
60 get_closest_feature(node.left, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
61 else: | |
62 if node.right: | |
63 get_closest_feature(node.right, direction, threshold_up, threshold_down, report_func_up, report_func_down) | |
64 | |
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65 |
0 | 66 def proximal_region_finder(readers, region, comments=True): |
67 """ | |
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68 Returns an iterator that yields elements of the form [ <original_interval>, <closest_feature> ]. |
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69 Intervals are GenomicInterval objects. |
0 | 70 """ |
71 primary = readers[0] | |
72 features = readers[1] | |
73 either = False | |
74 if region == 'Upstream': | |
75 up, down = True, False | |
76 elif region == 'Downstream': | |
77 up, down = False, True | |
78 else: | |
79 up, down = True, True | |
80 if region == 'Either': | |
81 either = True | |
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82 |
0 | 83 # Read features into memory: |
84 rightTree = quicksect.IntervalTree() | |
85 for item in features: | |
86 if type( item ) is GenomicInterval: | |
87 rightTree.insert( item, features.linenum, item ) | |
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88 |
0 | 89 for interval in primary: |
90 if type( interval ) is Header: | |
91 yield interval | |
92 if type( interval ) is Comment and comments: | |
93 yield interval | |
94 elif type( interval ) == GenomicInterval: | |
95 chrom = interval.chrom | |
96 start = int(interval.start) | |
97 end = int(interval.end) | |
98 strand = interval.strand | |
99 if chrom not in rightTree.chroms: | |
100 continue | |
101 else: | |
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102 root = rightTree.chroms[chrom] # root node for the chrom tree |
0 | 103 result_up = [] |
104 result_down = [] | |
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105 if (strand == '+' and up) or (strand == '-' and down): |
0 | 106 #upstream +ve strand and downstream -ve strand cases |
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107 get_closest_feature(root, 1, start, None, lambda node: result_up.append( node ), None) |
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108 |
0 | 109 if (strand == '+' and down) or (strand == '-' and up): |
110 #downstream +ve strand and upstream -ve strand case | |
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111 get_closest_feature(root, 0, None, end - 1, None, lambda node: result_down.append( node )) |
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112 |
0 | 113 if result_up: |
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114 if len(result_up) > 1: # The results_up list has a list of intervals upstream to the given interval. |
0 | 115 ends = [] |
116 for n in result_up: | |
117 ends.append(n.end) | |
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118 res_ind = ends.index(max(ends)) # fetch the index of the closest interval i.e. the interval with the max end from the results_up list |
0 | 119 else: |
120 res_ind = 0 | |
121 if not(either): | |
122 yield [ interval, result_up[res_ind].other ] | |
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123 |
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124 if result_down: |
0 | 125 if not(either): |
126 #The last element of result_down will be the closest element to the given interval | |
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127 yield [ interval, result_down[-1].other ] |
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128 |
0 | 129 if either and (result_up or result_down): |
130 iter_val = [] | |
131 if result_up and result_down: | |
132 if abs(start - int(result_up[res_ind].end)) <= abs(end - int(result_down[-1].start)): | |
133 iter_val = [ interval, result_up[res_ind].other ] | |
134 else: | |
135 #The last element of result_down will be the closest element to the given interval | |
136 iter_val = [ interval, result_down[-1].other ] | |
137 elif result_up: | |
138 iter_val = [ interval, result_up[res_ind].other ] | |
139 elif result_down: | |
140 #The last element of result_down will be the closest element to the given interval | |
141 iter_val = [ interval, result_down[-1].other ] | |
142 yield iter_val | |
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143 |
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144 |
0 | 145 def main(): |
146 options, args = doc_optparse.parse( __doc__ ) | |
147 try: | |
148 chr_col_1, start_col_1, end_col_1, strand_col_1 = parse_cols_arg( options.cols1 ) | |
149 chr_col_2, start_col_2, end_col_2, strand_col_2 = parse_cols_arg( options.cols2 ) | |
150 in1_gff_format = bool( options.gff1 ) | |
151 in2_gff_format = bool( options.gff2 ) | |
152 in_fname, in2_fname, out_fname, direction = args | |
153 except: | |
154 doc_optparse.exception() | |
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155 |
0 | 156 # Set readers to handle either GFF or default format. |
157 if in1_gff_format: | |
158 in1_reader_wrapper = GFFIntervalToBEDReaderWrapper | |
159 else: | |
160 in1_reader_wrapper = NiceReaderWrapper | |
161 if in2_gff_format: | |
162 in2_reader_wrapper = GFFIntervalToBEDReaderWrapper | |
163 else: | |
164 in2_reader_wrapper = NiceReaderWrapper | |
165 | |
166 g1 = in1_reader_wrapper( fileinput.FileInput( in_fname ), | |
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167 chrom_col=chr_col_1, |
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168 start_col=start_col_1, |
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169 end_col=end_col_1, |
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170 strand_col=strand_col_1, |
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171 fix_strand=True ) |
0 | 172 g2 = in2_reader_wrapper( fileinput.FileInput( in2_fname ), |
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173 chrom_col=chr_col_2, |
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174 start_col=start_col_2, |
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175 end_col=end_col_2, |
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176 strand_col=strand_col_2, |
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177 fix_strand=True ) |
0 | 178 |
179 # Find flanking features. | |
180 out_file = open( out_fname, "w" ) | |
181 try: | |
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182 for result in proximal_region_finder([g1, g2], direction): |
0 | 183 if type( result ) is list: |
184 line, closest_feature = result | |
185 # Need to join outputs differently depending on file types. | |
186 if in1_gff_format: | |
187 # Output is GFF with added attribute 'closest feature.' | |
188 | |
189 # Invervals are in BED coordinates; need to convert to GFF. | |
190 line = convert_bed_coords_to_gff( line ) | |
191 closest_feature = convert_bed_coords_to_gff( closest_feature ) | |
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192 |
0 | 193 # Replace double quotes with single quotes in closest feature's attributes. |
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194 out_file.write( "%s closest_feature \"%s\" \n" % |
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195 ( "\t".join( line.fields ), |
0 | 196 "\t".join( closest_feature.fields ).replace( "\"", "\\\"" ) |
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197 ) ) |
0 | 198 else: |
199 # Output is BED + closest feature fields. | |
200 output_line_fields = [] | |
201 output_line_fields.extend( line.fields ) | |
202 output_line_fields.extend( closest_feature.fields ) | |
203 out_file.write( "%s\n" % ( "\t".join( output_line_fields ) ) ) | |
204 else: | |
205 out_file.write( "%s\n" % result ) | |
206 except ParseError, exc: | |
207 fail( "Invalid file format: %s" % str( exc ) ) | |
208 | |
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209 print "Direction: %s" % (direction) |
0 | 210 if g1.skipped > 0: |
211 print skipped( g1, filedesc=" of 1st dataset" ) | |
212 if g2.skipped > 0: | |
213 print skipped( g2, filedesc=" of 2nd dataset" ) | |
214 | |
215 if __name__ == "__main__": | |
216 main() |