/usr/share/pyshared/cogent/parse/sprinzl.py is in python-cogent 1.5.3-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 | #/usr/bin/env python
"""Parsers for the Sprinzl tRNA databases.
"""
from cogent.util.misc import InverseDict
from string import strip, maketrans
from cogent.core.sequence import RnaSequence
from cogent.core.info import Info as InfoClass
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Jeremy Widmann", "Sandra Smit"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
def Rna(x, Info=None):
if isinstance(x, list):
x = ''.join(x)
if Info is None:
Info = {}
return RnaSequence(x.upper().replace('T','U'), Info=InfoClass(Info))
SprinzlFields =['Accession', 'AA', 'Anticodon', 'Species', 'Strain']
def OneLineSprinzlParser(infile):
"""Returns successive records from the tRNA database. First line labels.
This was the first attempt at the parser, and requires quite a lot of
preprocessing. Use SprinzlParser for something more general.
Works on a file obtained by the following method:
1. Do the default search.
2. Show all the columns and autofit them.
3. Delete the first column of numbers and all blank columns.
4. Name the first 5 columns "Accession, AA, Anticodon, Species, Strain".
5. Save the worksheet as plain text.
"""
first = True
for l in infile:
line = l.strip()
if not line:
continue
fields = line.split('\t')
if first: #label line
label_fields = fields[5:]
labels = InverseDict(enumerate(label_fields))
first = False
else:
info = dict(zip(SprinzlFields, map(strip, fields[0:5])))
info['Labels'] = labels
yield Rna(map(strip, fields[5:]), Info=info)
GenomicFields = ['', 'Accession', 'AA', '', 'Anticodon', '', 'Species', \
'', '', '', '', '', '', '', '', '', 'Strain', '', '', '', 'Taxonomy']
def _fix_structure(fields, seq):
"""Returns a string with correct # chars from db struct line.
fields should be the result of line.split('\t')
Implementation notes:
Pairing line uses strange format: = is pair, * is GU pair, and
nothing is unpaired. Cells are not padded out to the start or end of
the sequence length, presumably to infuriate the unwary.
I don't _think_ it's possible to convert these into ViennaStructures
since we don't know where each helix starts and ends, and the lengths
of each piece can vary. I'd be happy to be proven wrong on this...
For some reason, _sometimes_ spaces are inserted, and _sometimes_
the cells are left entirely blank. Also, when there's a noncanonical
pair in the helix, the helix is broken into two pieces, so counting
pieces isn't going to work for figuring out the ViennaStructure.
Expects as input the sequence and the raw structure line.
"""
num_blanks = 4
pieces = fields[num_blanks:]
result = ['.'] * len(seq)
for i, p in enumerate(pieces):
if p and (p != ' '):
result[i] = p
return ''.join(result)
def _fix_sequence(seq):
"""Returns string where terminal gaps are replaced with terminal CCA.
Some of the sequence in the Genomic tRNA Database have gaps where the
acceptor stem (terminal CCA) should be. This function checks the
number of terminal gaps and replaces with appropriate part of terminal
CCA.
"""
if seq.endswith('---'):
seq = seq[:-3]+'CCA'
elif seq.endswith('--'):
seq = seq[:-2]+'CA'
elif seq.endswith('-'):
seq = seq[:-1]+'A'
return seq
def GenomicSprinzlParser(infile,fix_sequence=False):
"""Parser for the Genomic tRNA Database.
Assumes the file has been prepared by the following method:
1. Set all search fields to empty.
2. Check all the results fields.
3. Perform the search (this takes a while).
4. Save the results worksheet as tab-delimited text.
Note that the alignment length is supposed to be 99 bases, but not all the
sequences have been padded out with the correct number of hyphens.
"""
num_blanks = 4
first = True
for l in infile:
#skip blank lines
line = l.rstrip()
if not line:
continue
fields = line.split('\t')
if first: #label line
#for unknown reasons, some of the field headers have '.' instead
#of '0', e.g. '7.' instead of '70'.
line = line.replace('.', '0')
fields = line.split('\t')
labels = InverseDict(enumerate(fields[num_blanks:]))
first = False
offset = 0
else: #expect 3 record lines at a time
if offset == 0: #label line
info = dict(zip(GenomicFields, map(strip, fields)))
#add in the labels
info['Labels'] = labels
#convert the taxonomy from a string to a list
info['Taxonomy'] = map(strip, info['Taxonomy'].split(';'))
#convert the anticodon into RNA
info['Anticodon'] = Rna(info['Anticodon'])
#get rid of the empty fields
del info['']
elif offset == 1: #sequence line
raw_seq = ''.join(map(strip, fields))
#for some reason, there are underscores in some sequences
raw_seq = raw_seq.replace('_', '-')
if fix_sequence:
raw_seq = _fix_sequence(raw_seq)
seq = Rna(raw_seq, Info=info)
elif offset == 2: #structure line
seq.Pairing = _fix_structure(fields, seq)
yield seq
#figure out which type of line we're expecting next
offset += 1
if offset > 2:
offset = 0
def get_pieces(struct, splits):
"""Breaks up the structure at fixed positions, returns the pieces.
struct: structure string in sprinzl format
splits: list or tuple of positions to split on
This is a helper function for the sprinzl_to_vienna function.
struct = '...===...===.'
splits = [0,3,7,-1,13]
pieces -> ['...','===.','..===','.']
"""
pieces = []
for x in range(len(splits)-1):
pieces.append(struct[splits[x]:splits[x+1]])
return pieces
def get_counts(struct_piece):
"""Returns a list of the lengths or the paired regions in the structure.
struct_pieces: string, piece of structure in sprinzl format
This is a helper function for the sprinzl_to_vienna function
struct_piece = '.===.=..'
returns [3,1]
"""
return map(len, filter(None, [i.strip('.') for i in \
struct_piece.split('.')]))
def sprinzl_to_vienna(sprinzl_struct):
"""Constructs vienna structure from sprinzl sec. structure format
sprinzl_struct: structure string in sprinzl format
Many things are hardcoded in here, so if the format or the alignment
changes, these values have to be adjusted!!!
The correctness of the splits has been tested on the GenomicDB
database from Jan 2006, containing 8163 sequences.
"""
assert len(sprinzl_struct) == 99
gu='*'
wc='='
splits = [0,8,19,29,38,55,79,-11,len(sprinzl_struct)]
direction = ['(','(',')','(',')','(',')',')']
#get structural pieces
s = sprinzl_struct.replace(gu,wc)
pieces = get_pieces(s, splits)
assert len(pieces) == len(splits)-1
#get counts of structured regions in each piece, check validity
counts = map(get_counts,pieces)
pairs = [(0,-1),(1,2),(3,4),(5,6)]
for i,j in pairs:
assert sum(counts[i]) == sum(counts[j])
#check counts matches directions
assert len(counts) == len(direction)
#construct string string of brackets
brackets = []
for lengths, br in zip(counts,direction):
for l in lengths:
brackets.append(l*br)
brackets = ''.join(brackets)
#build vienna structure
vienna = []
x=0
for sym in s:
if sym == '.':
vienna.append(sym)
else:
vienna.append(brackets[x])
x += 1
return ''.join(vienna)
|