def readComponents(options):
"""read components from filename supplied in the options.
"""
if options.filename_components:
map_seq_id2component =\
IOTools.ReadMap( open(options.filename_components, "r"),
columns = "all",
both_directions = False)
map_component2seq_id = {}
map_component2input_id = {}
for key, val in map_seq_id2component.items():
if type(val) == types.StringType:
input_id = val
output_id = val
elif type(val) == types.TupleType:
if len(val) == 2:
input_id = val[0]
output_id = val[1]
else:
input_id = val[0]
output_id = val[0]
else:
raise ValueError("error in reading %s: %s->%s" %
(options.filename_components, key, val))
if output_id not in map_component2seq_id:
map_component2seq_id[output_id] = []
map_component2seq_id[output_id].append(key)
map_component2input_id[output_id] = input_id
return map_seq_id2component, map_component2seq_id, map_component2input_id
else:
return None, None, None
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv == None: argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: split_fasta.py 1714 2007-12-11 16:51:12Z andreas $"
)
parser.add_option("-f",
"--file",
dest="input_filename",
type="string",
help="input filename. If not given, stdin is used.",
metavar="FILE")
parser.add_option(
"-i",
"--input-pattern",
dest="input_pattern",
type="string",
help="input pattern. Parses description line in order to extract id.")
parser.add_option(
"-o",
"--output-pattern",
dest="output_pattern",
type="string",
help="output pattern. Gives filename for a given sequence.")
parser.add_option(
"-n",
"--num-sequences",
dest="num_sequences",
type="int",
help="split by number of sequences (not implemented yet).")
parser.add_option("-m",
"--map",
dest="map_filename",
type="string",
help="map filename. Map identifiers to filenames",
metavar="FILE")
parser.add_option("-s",
"--skip-identifiers",
dest="skip_identifiers",
action="store_true",
help="do not write identifiers.",
metavar="FILE")
parser.add_option("--min-size",
dest="min_size",
type="int",
help="minimum cluster size.")
parser.set_defaults( \
input_filename = None,
map_filename = None,
skip_identifiers = False,
input_pattern = "^(\S+)",
min_size = 0,
num_sequences = None,
output_pattern = "%s" )
(options, args) = E.Start(parser)
if options.input_filename:
infile = IOTools.openFile(options.input_filename, "r")
else:
infile = sys.stdin
if options.map_filename:
map_id2filename = IOTools.ReadMap(open(options.map_filename, "r"))
else:
map_id2filename = {}
if options.num_sequences:
files = FilesChunks(chunk_size=options.num_sequences,
output_pattern=options.output_pattern,
skip_identifiers=options.skip_identifiers)
else:
files = Files(output_pattern=options.output_pattern,
skip_identifiers=options.skip_identifiers)
if options.input_pattern:
rx = re.compile(options.input_pattern)
else:
rx = None
ninput = 0
noutput = 0
identifier = None
chunk = 0
for seq in FastaIterator.iterate(infile):
ninput += 1
if rx:
try:
identifier = rx.search(seq.title).groups()[0]
except AttributeError:
print "# parsing error in description line %s" % (seq.title)
else:
identifier = seq.title
if map_id2filename:
if identifier in map_id2filename:
identifier = map_id2filename[identifier]
else:
continue
files.Write(identifier, seq)
noutput += 1
if options.input_filename:
infile.close()
## delete all clusters below a minimum size
## Note: this has to be done at the end, because
## clusters sizes are only available once both the fasta
## file and the map has been parsed.
if options.min_size:
ndeleted = files.DeleteFiles(min_size=options.min_size)
else:
ndeleted = 0
if options.loglevel >= 1:
print "# input=%i, output=%i, ndeleted=%i" % (ninput, noutput,
ndeleted)
E.Stop()
def Process(lines, other_trees, options, map_old2new, ntree):
nexus = TreeTools.Newick2Nexus(map(lambda x: x[:-1], lines))
if options.loglevel >= 1:
options.stdlog.write("# read %i trees.\n" % len(nexus.trees))
nskipped = 0
ntotal = len(nexus.trees)
extract_pattern = None
species2remove = None
write_map = False
phylip_executable = None
phylip_options = None
index = 0
# default: do not output internal node names
write_all_taxa = False
for tree in nexus.trees:
if options.outgroup:
tree.root_with_outgroup(options.outgroup)
for method in options.methods:
if options.loglevel >= 3:
options.stdlog.write("# applying method %s to tree %i.\n" %
(method, index))
if method == "midpoint-root":
tree.root_midpoint()
elif method == "balanced-root":
tree.root_balanced()
elif method == "unroot":
TreeTools.Unroot(tree)
elif method == "phylip":
if not phylip_executable:
phylip_executable = options.parameters[0]
del options.parameters[0]
phylip_options = re.split("@", options.parameters[0])
del options.parameters[0]
phylip = WrapperPhylip.Phylip()
phylip.setProgram(phylip_executable)
phylip.setOptions(phylip_options)
phylip.setTree(tree)
result = phylip.run()
nexus.trees[index] = result.mNexus.trees[0]
elif method == "normalize":
if options.value == 0:
v = 0
for n in tree.chain.keys():
v = max(v, tree.node(n).data.branchlength)
else:
v = options.value
for n in tree.chain.keys():
tree.node(n).data.branchlength /= float(options.value)
elif method == "divide-by-tree":
if len(other_trees) > 1:
other_tree = other_trees[ntree]
else:
other_tree = other_trees[0]
# the trees have to be exactly the same!!
if options.loglevel >= 2:
print tree.display()
print other_tree.display()
if not tree.is_identical(other_tree):
nskipped += 1
continue
# even if the trees are the same (in topology), the node numbering might not be
# the same. Thus build a map of node ids.
map_a2b = TreeTools.GetNodeMap(tree, other_tree)
for n in tree.chain.keys():
try:
tree.node(n).data.branchlength /= float(
other_tree.node(map_a2b[n]).data.branchlength)
except ZeroDivisionError:
options.stdlog.write(
"# Warning: branch for nodes %i and %i in tree-pair %i: divide by zero\n"
% (n, map_a2b[n], ntree))
continue
elif method == "rename":
if not map_old2new:
map_old2new = IOTools.ReadMap(open(options.parameters[0],
"r"),
columns=(0, 1))
if options.invert_map:
map_old2new = IOTools.getInvertedDictionary(
map_old2new, make_unique=True)
del options.parameters[0]
unknown = []
for n, node in tree.chain.items():
if node.data.taxon:
try:
node.data.taxon = map_old2new[node.data.taxon]
except KeyError:
unknown.append(node.data.taxon)
for taxon in unknown:
tree.prune(taxon)
# reformat terminals
elif method == "extract-with-pattern":
if not extract_pattern:
extract_pattern = re.compile(options.parameters[0])
del options.parameters[0]
for n in tree.get_terminals():
node = tree.node(n)
node.data.taxon = extract_pattern.search(
node.data.taxon).groups()[0]
elif method == "set-uniform-branchlength":
for n in tree.chain.keys():
tree.node(n).data.branchlength = options.value
elif method == "build-map":
# build a map of identifiers
options.write_map = True
for n in tree.get_terminals():
node = tree.node(n)
if node.data.taxon not in map_old2new:
new = options.template_identifier % (len(map_old2new) +
1)
map_old2new[node.data.taxon] = new
node.data.taxon = map_old2new[node.data.taxon]
elif method == "remove-pattern":
if species2remove is None:
species2remove = re.compile(options.parameters[0])
del options.parameters
taxa = []
for n in tree.get_terminals():
t = tree.node(n).data.taxon
skip = False
if species2remove.search(t):
continue
if not skip:
taxa.append(t)
TreeTools.PruneTree(tree, taxa)
elif method == "add-node-names":
inode = 0
write_all_taxa = True
for n, node in tree.chain.items():
if not node.data.taxon:
node.data.taxon = "inode%i" % inode
inode += 1
elif method == "newick2nhx":
# convert names to species names
for n in tree.get_terminals():
t = tree.node(n).data.taxon
d = t.split("|")
if len(d) >= 2:
tree.node(n).data.species = d[0]
index += 1
ntree += 1
if options.output_format == "nh":
options.stdout.write(
TreeTools.Nexus2Newick(
nexus,
write_all_taxa=True,
with_branchlengths=options.with_branchlengths) + "\n")
else:
for tree in nexus.trees:
tree.writeToFile(options.stdout, format=options.output_format)
return ntotal, nskipped, ntree
def main(argv=sys.argv):
parser = E.OptionParser(
version=
"%prog version: $Id: mali2mali.py 2782 2009-09-10 11:40:29Z andreas $",
usage=globals()["__doc__"])
parser.add_option(
"-i",
"--input-format",
dest="input_format",
type="choice",
choices=("plain", "fasta", "clustal", "stockholm", "phylip"),
help="input format of multiple alignment [default=%default].")
parser.add_option(
"-o",
"--output-format",
dest="output_format",
type="choice",
choices=("plain", "fasta", "stockholm", "phylip", "nexus",
"plain-fasta"),
help="output format of multiple alignment [default=%default].")
parser.add_option(
"--with-ranges",
dest="with_ranges",
action="store_true",
help=
"output alignment ranges (suffix /from-to after identifier) [default=%default]."
)
parser.add_option(
"--without-ranges",
dest="with_ranges",
action="store_false",
help=
"do not output alignment ranges (suffix /from-to after identifier) [default=%default]."
)
parser.add_option("-u",
"--allow-duplicates",
dest="allow_duplicates",
action="store_true",
help="permit duplicate entries [default=%default].")
parser.add_option(
"-m",
"--method",
dest="methods",
type="string",
help=
"""methods to apply. Several methods can be specified in a ','-separated list [default=%default]."""
)
parser.add_option(
"-p",
"--parameters",
dest="parameters",
type="string",
help="parameter stack for methods that require one [default=%default]."
)
parser.add_option(
"-a",
"--mask-char",
dest="mask_char",
type="string",
help="character to identify/set masked characters [default=%default].")
parser.set_defaults(
input_format="fasta",
output_format="fasta",
methods="",
parameters="",
mask_char="x",
gap_chars="-.nN",
with_ranges=True,
allow_duplicates=False,
)
(options, args) = E.Start(parser)
options.methods = options.methods.split(",")
options.parameters = options.parameters.split(",")
# 1. read multiple alignment in various formats
if options.allow_duplicates:
mali = Mali.SequenceCollection()
else:
mali = Mali.Mali()
t1 = time.time()
mali.readFromFile(options.stdin, format=options.input_format)
E.info("read mali with %i entries in %i seconds." %
(len(mali), time.time() - t1))
if len(mali) == 0:
raise ValueError("empty multiple alignment")
for method in options.methods:
t1 = time.time()
if method == "remove-unaligned-ends":
mali.removeUnalignedEnds()
elif method == "remove-end-gaps":
mali.removeEndGaps()
elif method == "remove-all-gaps":
mali.removeGaps(minimum_gaps=len(mali))
elif method == "remove-any-gaps":
mali.removeGaps(minimum_gaps=1)
elif method == "remove-some-gaps":
minimum_gaps = int(options.parameters[0])
del options.parameters[0]
mali.removeGaps(minimum_gaps=minimum_gaps)
elif method == "remove-empty-sequences":
mali.removeEmptySequences()
elif method == "upper":
mali.upperCase()
elif method == "lower":
mali.lowerCase()
elif method == "mark-codons":
mali.markCodons()
elif method == "remove-stops":
mali.removePattern(lambda x: x.upper() in ("TAG", "TAA", "TGA"),
allowed_matches=0,
minimum_matches=1,
delete_frame=3,
search_frame=3)
elif method == "shift-alignment":
map_id2offset = IOTools.ReadMap(open(options.parameters[0], "r"),
map_functions=(str, int))
del options.parameters[0]
mali.shiftAlignment(map_id2offset)
elif method == "propagate-masks":
mali.propagateMasks(mask_char=options.mask_char)
elif method == "recount":
mali.recount()
elif method in ("mark-transitions", "filter-odd-transitions",
"filter-even-transitions", "keep-even-segments",
"keep-odd-segments"):
if os.path.exists(options.parameters[0]):
map_id2transitions = IOTools.readMultiMap(
open(options.parameters[0], "r"), map_functions=(str, int))
else:
map_id2transitions = {}
r = map(int, options.parameters[0].split(':'))
r.sort()
map_id2transitions["mali"] = r
del options.parameters[0]
if method == "mark-transitions":
mali.markTransitions(map_id2transitions)
elif method in ("filter-odd-transitions", "keep-even-segments"):
mali.markTransitions(map_id2transitions, mode="keep-odd")
elif method in ("filter-even-transitions", "keep-odd-segments"):
mali.markTransitions(map_id2transitions, mode="keep-even")
elif method == "propagate-transitions":
mali.propagateTransitions()
elif method == "map-annotation":
# map annotations in one mali (stockholm-format) to the annotations in another.
# Note: the first two sequence identifiers must be shared and the sequence of the
# same length
other_mali = Mali.Mali()
other_mali.readFromFile(open(options.parameters[0], "r"),
format="stockholm")
del options.parameters[0]
mali.copyAnnotations(other_mali)
elif method == "add-annotation":
annotation_type, annotation_file = options.parameters[:2]
del options.parameters[:2]
AddAnnotation(mali, annotation_type, annotation_file)
elif method == "mask-columns":
annotation_type, annotation_file = options.parameters[:2]
del options.parameters[:2]
maskColumns(mali, annotation_type, annotation_file)
elif method == "remove-unaligned-pairs":
removeUnalignedPairs(mali, options)
elif method == "filter-3rd":
filterMali(mali, "3rd")
elif method == "filter-4d":
filterMali(mali, "4d")
elif method in ("mask-seg", "mask-bias"):
a, b = method.split("-")
maskMali(mali, b)
elif method == "exclude-with-stop":
mali.filter(method="with-stop")
elif method == "exclude-with-stop":
mali.filter(method="with-frameshift")
E.info("applied method %s in %i seconds." % (method, time.time() - t1))
mali.writeToFile(options.stdout,
format=options.output_format,
write_ranges=options.with_ranges)
E.Stop()
help="aggregation function.")
parser.set_defaults(filename_map=None,
filename_info=None,
filename_tissues=None,
headers=True,
aggregate="mean",
value_format="%5.2f",
method="counts")
(options, args) = E.Start(parser)
if not options.filename_map:
raise "please supply filename mapping probesets to identifiers."
map_probe2locus = IOTools.ReadMap(open(options.filename_map, "r"))
matrix, row_headers, col_headers = MatlabTools.readMatrix(
sys.stdin, format="full", headers=options.headers)
if options.filename_tissues:
tissues, nerrors = IOTools.ReadList(open(options.filename_tissues,
"r"))
tissues = set(tissues)
columns = []
for x in range(len(col_headers)):
if col_headers[x] in tissues:
columns.append(x)
else:
columns = range(len(col_headers))
def main(argv=None):
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option(
"-w",
"--weights-tsv-file",
dest="filename_weights",
type="string",
help="filename with codon frequencies. Multiple filenames "
"can be separated by comma.")
parser.add_option("-s",
"--section",
dest="sections",
type="choice",
action="append",
choices=("length", "sequence", "hid", "na", "aa", "cpg",
"dn", "degeneracy", "gaps", "codons",
"codon-usage", "codon-translator",
"codon-bias"),
help="which sections to output [%default]")
parser.add_option(
"-t",
"--sequence-type",
dest="seqtype",
type="choice",
choices=("na", "aa"),
help="type of sequence: na=nucleotides, aa=amino acids [%default].")
parser.add_option(
"-e",
"--regex-identifier",
dest="regex_identifier",
type="string",
help="regular expression to extract identifier from fasta "
"description line.")
parser.add_option("--split-fasta-identifier",
dest="split_id",
action="store_true",
help="split fasta description line (starting >) and use "
"only text before first space")
parser.add_option(
"--add-total",
dest="add_total",
action="store_true",
help="add a row with column totals at the end of the table"
"[%default]")
parser.set_defaults(
filename_weights=None,
pseudocounts=1,
sections=[],
regex_identifier="(.+)",
seqtype="na",
gap_chars='xXnN',
split_id=False,
add_total=False,
)
(options, args) = E.Start(parser, argv=argv)
rx = re.compile(options.regex_identifier)
reference_codons = []
if options.filename_weights:
options.filename_weights = options.filename_weights.split(",")
for filename in options.filename_weights:
if filename == "uniform":
reference_codons.append(Genomics.GetUniformCodonUsage())
else:
reference_codons.append(
IOTools.ReadMap(IOTools.openFile(filename, "r"),
has_header=True,
map_functions=(str, float)))
# print codon table differences
options.stdlog.write(
"# Difference between supplied codon usage preferences.\n")
for x in range(0, len(reference_codons)):
for y in range(0, len(reference_codons)):
if x == y:
continue
# calculate KL distance
a = reference_codons[x]
b = reference_codons[y]
d = 0
for codon, p in a.items():
if Genomics.IsStopCodon(codon):
continue
d += b[codon] * math.log(b[codon] / p)
options.stdlog.write("# tablediff\t%s\t%s\t%f\n" %
(options.filename_weights[x],
options.filename_weights[y], d))
iterator = FastaIterator.FastaIterator(options.stdin)
def getCounter(section):
if options.seqtype == "na":
if section == "length":
s = SequenceProperties.SequencePropertiesLength()
elif section == "sequence":
s = SequenceProperties.SequencePropertiesSequence()
elif section == "hid":
s = SequenceProperties.SequencePropertiesHid()
elif section == "na":
s = SequenceProperties.SequencePropertiesNA()
elif section == "gaps":
s = SequenceProperties.SequencePropertiesGaps(
options.gap_chars)
elif section == "cpg":
s = SequenceProperties.SequencePropertiesCpg()
elif section == "dn":
s = SequenceProperties.SequencePropertiesDN()
# these sections requires sequence length to be a multiple of 3
elif section == "aa":
s = SequenceProperties.SequencePropertiesAA()
elif section == "degeneracy":
s = SequenceProperties.SequencePropertiesDegeneracy()
elif section == "codon-bias":
s = SequenceProperties.SequencePropertiesBias(reference_codons)
elif section == "codons":
s = SequenceProperties.SequencePropertiesCodons()
elif section == "codon-usage":
s = SequenceProperties.SequencePropertiesCodonUsage()
elif section == "codon-translator":
s = SequenceProperties.SequencePropertiesCodonTranslator()
else:
raise ValueError("unknown section %s" % section)
elif options.seqtype == "aa":
if section == "length":
s = SequenceProperties.SequencePropertiesLength()
elif section == "sequence":
s = SequenceProperties.SequencePropertiesSequence()
elif section == "hid":
s = SequenceProperties.SequencePropertiesHid()
elif section == "aa":
s = SequenceProperties.SequencePropertiesAminoAcids()
else:
raise ValueError("unknown section %s" % section)
return s
# setup totals
totals = {}
for section in options.sections:
totals[section] = getCounter(section)
options.stdout.write("id")
for section in options.sections:
options.stdout.write("\t" + "\t".join(totals[section].getHeaders()))
options.stdout.write("\n")
options.stdout.flush()
s = getCounter("hid")
s.loadSequence("AAAAAAAAA", "na")
for cur_record in iterator:
sequence = re.sub(" ", "", cur_record.sequence).upper()
if len(sequence) == 0:
raise ValueError("empty sequence %s" % cur_record.title)
id = rx.search(cur_record.title).groups()[0]
if options.split_id is True:
options.stdout.write("%s" % id.split()[0])
else:
options.stdout.write("%s" % id)
options.stdout.flush()
for section in options.sections:
s = getCounter(section)
s.loadSequence(sequence, options.seqtype)
totals[section].addProperties(s)
options.stdout.write("\t" + "\t".join(s.getFields()))
options.stdout.write("\n")
if options.add_total:
options.stdout.write("total")
for section in options.sections:
options.stdout.write("\t" + "\t".join(totals[section].getFields()))
options.stdout.write("\n")
E.Stop()
def main(argv=None):
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version",
usage=globals()["__doc__"])
parser.add_option(
"-m",
"--method",
dest="methods",
type="choice",
action="append",
choices=("translate", "translate-to-stop", "truncate-at-stop",
"back-translate", "mark-codons", "apply-map", "build-map",
"pseudo-codons", "filter", "interleaved-codons", "map-codons",
"remove-gaps", "mask-seg", "mask-bias", "mask-codons",
"mask-incomplete-codons", "mask-stops", "mask-soft",
"remove-stops", "upper", "lower", "reverse-complement",
"sample", "shuffle"),
help="method to apply to sequences.")
parser.add_option("-p",
"--parameters",
dest="parameters",
type="string",
help="parameter stack for methods that require one "
"[default=%default].")
parser.add_option("-x",
"--ignore-errors",
dest="ignore_errors",
action="store_true",
help="ignore errors [default = %default].")
parser.add_option("--sample-proportion",
dest="sample_proportion",
type="float",
help="sample proportion [default = %default].")
parser.add_option("--exclude-pattern",
dest="exclude_pattern",
type="string",
help="exclude all sequences with ids matching pattern "
"[default = %default].")
parser.add_option("--include-pattern",
dest="include_pattern",
type="string",
help="include only sequences with ids matching pattern "
"[default = %default].")
parser.add_option("--filter-method",
dest="filter_methods",
type="string",
action="append",
help="filtering methods to apply "
"[default = %default].")
parser.add_option(
"-t",
"--sequence-type",
dest="type",
type="choice",
choices=("aa", "na"),
help="sequence type (aa or na) [%default]. This option determines "
"which characters to use for masking [default = %default].")
parser.add_option(
"-l",
"--template-identifier",
dest="template_identifier",
type="string",
help="template for numerical identifier [default = %default] "
"for the operation --build-map. A %i is replaced by the position "
"of the sequence in the file.")
parser.set_defaults(
methods=[],
parameters="",
type="na",
aa_mask_chars="xX",
aa_mask_char="x",
na_mask_chars="nN",
na_mask_char="n",
gap_chars="-.",
gap_char="-",
template_identifier="ID%06i",
ignore_errors=False,
exclude_pattern=None,
include_pattern=None,
sample_proportion=None,
filter_methods=[],
)
(options, args) = E.Start(parser)
options.parameters = options.parameters.split(",")
rx_include, rx_exclude = None, None
if options.include_pattern:
rx_include = re.compile(options.include_pattern)
if options.exclude_pattern:
rx_exclude = re.compile(options.exclude_pattern)
iterator = FastaIterator.FastaIterator(options.stdin)
nseq = 0
map_seq2nid = {}
if "apply-map" in options.methods:
map_seq2nid = IOTools.ReadMap(open(options.parameters[0], "r"))
del options.parameters[0]
if options.type == "na":
mask_chars = options.na_mask_chars
mask_char = options.na_mask_char
else:
mask_chars = options.aa_mask_chars
mask_char = options.aa_mask_char
if "map-codons" in options.methods:
map_codon2code = IOTools.ReadMap(open(options.parameters[0], "r"))
del options.parameters[0]
if "mask-soft" in options.methods:
f = options.parameters[0]
del options.parameters[0]
hard_masked_iterator = FastaIterator.FastaIterator(open(f, "r"))
if "mask-codons" in options.methods or "back-translate" in options.methods:
# open a second stream to read sequences from
f = options.parameters[0]
del options.parameters[0]
other_iterator = FastaIterator.FastaIterator(open(f, "r"))
ninput, noutput, nerrors, nskipped = 0, 0, 0, 0
if "sample" in options.methods:
if not options.sample_proportion:
raise ValueError("specify a sample proportion")
sample_proportion = options.sample_proportion
else:
sample_proportion = None
filter_min_sequence_length = None
filter_max_sequence_length = None
filter_id_list = None
for f in options.filter_methods:
if f.startswith("min-length"):
filter_min_sequence_length = int(f.split("=")[1])
elif f.startswith("max-length"):
filter_max_sequence_length = int(f.split("=")[1])
elif f.startswith("id-file"):
filter_id_list = [
line[:-1] for line in IOTools.openFile(f.split("=")[1])
]
def raiseIfNotCodon(l, title):
'''raise ValueError if sequence length l is not divisible by
3'''
if l % 3 != 0:
raise ValueError("length of sequence %s not divisible by 3" %
(title))
while 1:
try:
cur_record = next(iterator)
except StopIteration:
break
if cur_record is None:
break
nseq += 1
ninput += 1
sequence = re.sub(" ", "", cur_record.sequence)
l = len(sequence)
if rx_include and not rx_include.search(cur_record.title):
nskipped += 1
continue
if rx_exclude and rx_exclude.search(cur_record.title):
nskipped += 1
continue
if sample_proportion:
if random.random() > sample_proportion:
continue
if not (filter_id_list is None or cur_record.title in filter_id_list):
nskipped += 1
continue
for method in options.methods:
if method == "translate":
# translate such that gaps are preserved
seq = []
ls = len(re.sub('[%s]' % options.gap_chars, sequence, ""))
if ls % 3 != 0:
msg = "length of sequence %s (%i) not divisible by 3" % (
cur_record.title, ls)
nerrors += 1
if options.ignore_errors:
E.warn(msg)
continue
else:
raise ValueError(msg)
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
aa = Genomics.MapCodon2AA(codon)
seq.append(aa)
sequence = "".join(seq)
elif method == "back-translate":
# translate from an amino acid alignment to codon alignment
seq = []
try:
other_record = next(other_iterator)
except StopIteration:
raise ValueError("run out of sequences")
if cur_record.title != other_record.title:
raise "sequence titles don't match: %s %s" % (
cur_record.title, other_record.title)
other_sequence = re.sub("[ %s]" % options.gap_chars, "",
other_record.sequence)
if len(other_sequence) % 3 != 0:
raise ValueError(
"length of sequence %s not divisible by 3" %
(other_record.title))
r = re.sub("[%s]" % options.gap_chars, "", sequence)
if len(other_sequence) != len(r) * 3:
raise ValueError(
"length of sequences do not match: %i vs %i" %
(len(other_sequence), len(r)))
x = 0
for aa in sequence:
if aa in options.gap_chars:
c = options.gap_char * 3
else:
c = other_sequence[x:x + 3]
x += 3
seq.append(c)
sequence = "".join(seq)
elif method == "pseudo-codons":
raiseIfNotCodon(l, cur_record.title)
seq = []
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
aa = Genomics.MapCodon2AA(codon)
seq.append(aa)
sequence = " ".join(seq)
elif method == "reverse-complement":
sequence = string.translate(
sequence, string.maketrans("ACGTacgt", "TGCAtgca"))[::-1]
elif method in ("mask-stops", "remove-stops"):
c = []
codon = []
new_sequence = []
if method == "mask-stops":
char = options.na_mask_char
elif method == "remove-stops":
char = options.gap_char
for x in sequence:
if x not in options.gap_chars:
codon.append(x.upper())
c.append(x)
if len(codon) == 3:
codon = "".join(codon).upper()
# mask all non-gaps
if Genomics.IsStopCodon(codon):
for x in c:
if x in options.gap_chars:
new_sequence.append(x)
else:
new_sequence.append(char)
else:
new_sequence += c
c = []
codon = []
new_sequence += c
sequence = "".join(new_sequence)
elif method == "mask-soft":
# Get next hard masked record and extract sequence and length
try:
cur_hm_record = next(hard_masked_iterator)
except StopIteration:
break
hm_sequence = re.sub(" ", "", cur_hm_record.sequence)
lhm = len(hm_sequence)
new_sequence = []
# Check lengths of unmasked and soft masked sequences the same
if l != lhm:
raise ValueError(
"length of unmasked and hard masked sequences not "
"identical for record %s" % (cur_record.title))
# Check if hard masked seq contains repeat (N), if so replace N
# with lowercase sequence from unmasked version
if sequence == hm_sequence:
pass
else:
for x, y in zip_longest(sequence, hm_sequence):
if y == "N":
new_sequence += x.lower()
else:
new_sequence += x.upper()
sequence = "".join(new_sequence)
elif method == "map-codons":
raiseIfNotCodon(l, cur_record.title)
seq = []
for codon in (sequence[x:x + 3].upper()
for x in range(0, l, 3)):
if codon not in map_codon2code:
aa = "X"
else:
aa = map_codon2code[codon]
seq.append(aa)
sequence = "".join(seq)
elif method == "interleaved-codons":
raiseIfNotCodon(l, cur_record.title)
seq = []
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
aa = Genomics.MapCodon2AA(codon)
seq.append("%s:%s" % (aa, codon))
sequence = " ".join(seq)
elif method == "translate-to-stop":
seq = []
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
if Genomics.IsStopCodon(codon):
break
aa = Genomics.MapCodon2AA(codon)
seq.append(aa)
sequence = "".join(seq)
elif method == "truncate-at-stop":
seq = []
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
if Genomics.IsStopCodon(codon):
break
seq.append(codon)
sequence = "".join(seq)
elif method == "remove-gaps":
seq = []
for s in sequence:
if s in options.gap_chars:
continue
seq.append(s)
sequence = "".join(seq)
elif method == "upper":
sequence = sequence.upper()
elif method == "lower":
sequence = sequence.lower()
elif method == "mark-codons":
raiseIfNotCodon(l, cur_record.title)
seq = []
sequence = " ".join(
[sequence[x:x + 3] for x in range(0, l, 3)])
elif method == "apply-map":
id = re.match("^(\S+)", cur_record.title).groups()[0]
if id in map_seq2nid:
rest = cur_record.title[len(id):]
cur_record.title = map_seq2nid[id] + rest
elif method == "build-map":
# build a map of identifiers
id = re.match("^(\S+)", cur_record.title).groups()[0]
new_id = options.template_identifier % nseq
if id in map_seq2nid:
raise "duplicate fasta entries - can't map those: %s" % id
map_seq2nid[id] = new_id
cur_record.title = new_id
elif method == "mask-bias":
masker = Masker.MaskerBias()
sequence = masker(sequence)
elif method == "mask-seg":
masker = Masker.MaskerSeg()
sequence = masker(sequence)
elif method == "shuffle":
s = list(sequence)
random.shuffle(s)
sequence = "".join(s)
elif method == "mask-incomplete-codons":
seq = list(sequence)
for x in range(0, l, 3):
nm = len([x for x in seq[x:x + 3] if x in mask_chars])
if 0 < nm < 3:
seq[x:x + 3] = [mask_char] * 3
sequence = "".join(seq)
elif method == "mask-codons":
# mask codons based on amino acids given as reference
# sequences.
other_record = next(other_iterator)
if other_record is None:
raise ValueError("run out of sequences.")
if cur_record.title != other_record.title:
raise ValueError("sequence titles don't match: %s %s" %
(cur_record.title, other_record.title))
other_sequence = re.sub(" ", "", other_record.sequence)
if len(other_sequence) * 3 != len(sequence):
raise ValueError(
"sequences for %s don't have matching lengths %i - %i"
% (cur_record.title, len(other_sequence) * 3,
len(sequence)))
seq = list(sequence)
c = 0
for x in other_sequence:
if x in options.aa_mask_chars:
if x.isupper():
seq[c:c + 3] = [options.na_mask_char.upper()] * 3
else:
seq[c:c + 3] = [options.na_mask_char.lower()] * 3
c += 3
sequence = "".join(seq)
l = len(sequence)
if filter_min_sequence_length is not None and \
l < filter_min_sequence_length:
nskipped += 1
if filter_max_sequence_length is not None and \
l > filter_max_sequence_length:
nskipped += 1
continue
options.stdout.write(">%s\n%s\n" % (cur_record.title, sequence))
noutput += 1
if "build-map" in options.methods:
p = options.parameters[0]
if p:
outfile = IOTools.openFile(p, "w")
else:
outfile = options.stdout
outfile.write("old\tnew\n")
for old_id, new_id in list(map_seq2nid.items()):
outfile.write("%s\t%s\n" % (old_id, new_id))
if p:
outfile.close()
E.info("ninput=%i, noutput=%i, nskipped=%i, nerrors=%i" %
(ninput, noutput, nskipped, nerrors))
E.Stop()
def main():
parser = E.OptionParser(
version=
"%prog version: $Id: plot_tree.py 2782 2009-09-10 11:40:29Z andreas $")
parser.add_option("-i",
"--title",
dest="title",
type="string",
help="page title.")
parser.add_option("-f",
"--footer",
dest="footer",
type="string",
help="page footer.")
parser.add_option("-s",
"--filename-tree",
dest="filename_tree",
type="string",
help="filename with tree.")
parser.add_option("-t", "--tree", dest="tree", type="string", help="tree.")
parser.add_option(
"-r",
"--species-regex",
dest="species_regex",
type="string",
help="regular expression to extract species from identifier.")
parser.add_option("--colour-by-species",
dest="colour_by_species",
action="store_true",
help="colour by species.")
parser.add_option("--support-style",
dest="support_style",
type="choice",
choices=("pie", "number"),
help="style for support information.")
parser.add_option("--error-style",
dest="error_style",
type="choice",
choices=("pie", "number"),
help="style for error information.")
parser.add_option("--branch-scale",
dest="branch_scale",
type="float",
help="branch length scale factor.")
parser.add_option("--height-scale",
dest="height_scale",
type="float",
help="height scale factor.")
parser.add_option("-a",
"--annotations",
dest="annotations",
type="choice",
action="append",
choices=("support", "error", "kaks", "master", "value",
"tables"),
help="annotations given by further trees.")
parser.add_option(
"--filename-tables",
dest="filename_tables",
type="string",
help="add tables from file (need also set options -a tables) [%default]"
)
parser.add_option("--show-branchlengths",
dest="show_branchlengths",
action="store_true",
help="show branch lengths.")
parser.add_option("--leaf-symbol",
dest="plot_leaf_symbol",
type="choice",
choices=("square", "circle"),
help="Symbol for leaves.")
parser.add_option("--font-size-branches",
dest="font_size_branches",
type="int",
help="set font size for branches.")
parser.add_option("--font-size-tips",
dest="font_size_tips",
type="int",
help="set font size for tips.")
parser.add_option("--font-style-tips",
dest="font_style_tips",
type="choice",
choices=(
"normal",
"italic",
),
help="set font style for tips.")
parser.add_option("--filename-map",
dest="filename_map",
type="string",
help="filename with a name translation table.")
parser.add_option("--filename-map-species2colour",
dest="filename_colour_map",
type="string",
help="filename with a map of species to colour.")
parser.add_option("--no-leaf-labels",
dest="plot_leaf_labels",
action="store_false",
help="do not show labels at leafs.")
parser.add_option("--no-ruler",
dest="plot_ruler",
action="store_false",
help="do not plot ruler.")
parser.set_defaults(
titles="",
title="",
footer="",
filename_tree=None,
species_regex="^([^|]+)\|",
colour_by_species=None,
tree=None,
branch_scale=0,
height_scale=0,
support_style=None,
error_style="number",
kaks_style="number",
annotations=None,
show_branchlengths=False,
branch_length_format="%5.2f",
font_size_tips=None,
font_size_branches=None,
font_style_tips=None,
filename_map=None,
filename_colour_map=None,
plot_leaf_labels=True,
plot_leaf_symbol=None,
plot_ruler=True,
filename_tables=None,
)
(options, args) = E.Start(parser, add_pipe_options=True)
if options.filename_tree:
tree_lines = open(options.filename_tree, "r").readlines()
elif options.tree:
tree_lines = options.tree
else:
tree_lines = sys.stdin.readlines()
nexus = TreeTools.Newick2Nexus(tree_lines)
master_tree = nexus.trees[0]
if options.filename_map:
map_names = IOTools.ReadMap(open(options.filename_map, "r"))
for id, node in master_tree.chain.items():
if node.data.taxon in map_names:
node.data.taxon = map_names[node.data.taxon]
if options.loglevel >= 2:
master_tree.display()
plot = SVGTree.SVGTree(master_tree)
if options.branch_scale:
plot.setBranchScale(options.branch_scale)
if options.height_scale != None:
plot.setHeightScale(options.height_scale)
if options.font_size_tips != None:
plot.setFontSize(options.font_size_tips)
if options.plot_ruler == False:
plot.setRulerElements([])
if options.show_branchlengths:
b = SVGTree.BranchDecoratorHorizontalBranchLength(master_tree)
if options.font_size_branches:
b.setFontSize(options.font_size_branches)
plot.setDecoratorHorizontalBranches(b)
if options.colour_by_species:
if options.filename_colour_map:
map_species2colour = IOTools.ReadMap(
open(options.filename_colour_map, "r"))
else:
map_species2colour = None
rx = re.compile(options.species_regex)
extract_species = lambda x: rx.search(x).groups()[0]
plot.setDecoratorExternalNodes(
SVGTree.NodeDecoratorBySpecies(
master_tree,
plot_symbol=options.plot_leaf_symbol,
plot_label=options.plot_leaf_labels,
map_species2colour=map_species2colour,
extract_species=extract_species))
if options.font_style_tips:
plot.getDecoratorExternalNodes().setFontStyle(options.font_style_tips)
plot.getDecoratorExternalNodes().setPlotLabel(options.plot_leaf_labels)
current_tree = 1
## add annotations by further trees given on the command line
branch_length_annotations = []
current_reference_tree = master_tree
if options.annotations:
for annotation in options.annotations:
tree = nexus.trees[current_tree]
if annotation == "support":
tree.branchlength2support()
for id, node in tree.chain.items():
node.data.branchlength = 1.0
if options.support_style == "pie":
plot.setDecoratorInternalNodes(
NodeDecoratorSupportPieChart(
nexus.trees[current_tree]))
elif annotation == "error":
if options.error_style == "number":
b = SVGTree.BranchDecoratorHorizontalBranchLengthError(
current_reference_tree, tree)
if options.font_size_branches:
b.setFontSize(options.font_size_branches)
branch_length_annotations.append(b)
elif annotation == "kaks":
if options.kaks_style == "number":
b = SVGTree.BranchDecoratorHorizontalBranchLengthWithKaks(
current_reference_tree, tree)
if options.font_size_branches:
b.setFontSize(options.font_size_branches)
branch_length_annotations.append(b)
elif annotation == "value":
b = SVGTree.BranchDecoratorHorizontalBranchLength(tree)
if options.font_size_branches:
b.setFontSize(options.font_size_branches)
branch_length_annotations.append(b)
elif annotation == "master":
current_reference_tree = tree
elif annotation == "tables":
b = BranchDecoratorTable(tree,
filename=options.filename_tables)
plot.setDecoratorHorizontalBranches(b)
current_tree += 1
if len(branch_length_annotations) == 1:
b = branch_length_annotations[0]
elif len(branch_length_annotations) == 2:
b1, b2 = branch_length_annotations
b1.setFontColour(SVGTree.BLUE)
b2.setFontColour(SVGTree.RED)
b = SVGTree.BranchDecoratorHorizontalAboveBelow(
master_tree, b1, b2)
elif len(branch_length_annotations) > 2:
raise "obtained more than three branch length annotations. Layout not implemented"
plot.setDecoratorHorizontalBranches(b)
plot.initializePlot()
plot.writeToFile(sys.stdout)
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: compare_clusters.py 2782 2009-09-10 11:40:29Z andreas $"
)
parser.add_option("-o",
"--output-pattern",
dest="output_pattern",
type="string",
help="output pattern for filenames.")
parser.set_defaults(
output_pattern=None,
format="%5.2f",
)
(options, args) = E.Start(parser, add_pipe_options=True)
if len(args) != 2:
raise "please supply to filenames with the clusters."
map_id2cluster1, map_cluster2ids1 = IOTools.ReadMap(open(args[0]),
both_directions=True)
map_id2cluster2, map_cluster2ids2 = IOTools.ReadMap(open(args[1]),
both_directions=True)
graph = networkx.Graph()
for a in map_cluster2ids1.keys():
graph.add_node((1, a))
for b in map_cluster2ids2.keys():
graph.add_node((2, b))
# build graph between clusters
for cluster1, ids1 in map_cluster2ids1.items():
for id1 in ids1:
if id1 in map_id2cluster2:
graph.add_edge((1, cluster1), (2, map_id2cluster2[id1]))
components = networkx.connected_components(graph)
#######################################################
#######################################################
#######################################################
# write components and compute counts
#######################################################
outfile = getFile("components", options)
outfile.write("id\ttotal\tn1\tn2\tmembers1\tmembers2\n")
n = 0
counts = {}
subsets = []
for component in components:
m1, m2 = [], []
for x in component:
if x[0] == 1:
m1.append(x[1])
else:
m2.append(x[1])
t = len(component)
n1 = len(m1)
n2 = len(m2)
cc = (n1, n2)
if cc not in counts:
counts[cc] = 0
counts[cc] += 1
if cc == (1, 1):
subsets.append(n)
n += 1
outfile.write("%i\t%i\t%i\t%i\t%s\t%s\n" %
(n, t, n1, n2, ",".join(m1), ",".join(m2)))
if outfile != options.stdout:
outfile.close()
else:
outfile.write("//\n")
#######################################################
#######################################################
#######################################################
# write counts
#######################################################
outfile = getFile("counts", options)
outfile.write("n1\tn2\tcounts\tpcounts1\tpcounts2\n")
for cc, c in counts.items():
outfile.write(
"%i\t%i\t%i\t%s\t%s\n" %
(cc[0], cc[1], c, options.format %
(100.0 * float(c) / len(map_cluster2ids1)), options.format %
(100.0 * float(c) / len(map_cluster2ids2))))
if outfile != options.stdout:
outfile.close()
else:
outfile.write("//\n")
#######################################################
#######################################################
#######################################################
# analyze subsets - how many of the 1:1 clusters
# contain the exact members?
#######################################################
outfile = getFile("subsets", options)
outfile.write("id\tn1\tn2\tunion\tinter\tunique1\tunique2\n")
ntrue = 0
nrest1 = 0
nrest2 = 0
nother = 0
for component_id in subsets:
component = components[component_id]
if component[0][0] == 1:
id1, id2 = component[0][1], component[1][1]
else:
id1, id2 = component[1][1], component[0][1]
members1 = set(map_cluster2ids1[id1])
members2 = set(map_cluster2ids2[id2])
union = len(members1.union(members2))
intersection = len(members1.intersection(members2))
rest1 = len(members1.difference(members2))
rest2 = len(members2.difference(members1))
if rest1 == 0 and rest2 == 0:
ntrue += 1
elif rest1 == 0:
nrest1 += 1
elif rest2 == 0:
nrest2 += 1
else:
nother += 1
outfile.write("%i\t%i\t%i\t%i\t%i\t%i\t%i\n" %
(component_id, len(members1), len(members2), union,
intersection, rest1, rest2))
if outfile != options.stdout:
outfile.close()
else:
outfile.write("//\n")
# write subset statistics
ntotal = len(subsets)
options.stdout.write("# subset statistics of 1:1 corresponding clusters\n")
options.stdout.write("class\tcounts\ttotal\n")
options.stdout.write("%s\t%i\t%s\n" %
("total", ntotal, options.format % 100))
options.stdout.write("%s\t%i\t%s\n" % ("true", ntrue, options.format %
(100.0 * ntrue / ntotal)))
options.stdout.write("%s\t%i\t%s\n" % ("unique1", nrest1, options.format %
(100.0 * nrest1 / ntotal)))
options.stdout.write("%s\t%i\t%s\n" % ("unique2", nrest2, options.format %
(100.0 * nrest2 / ntotal)))
options.stdout.write("%s\t%i\t%s\n" % ("other", nother, options.format %
(100.0 * nother / ntotal)))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: gpipe/analyze_queries.py 2781 2009-09-10 11:33:14Z andreas $"
)
parser.add_option("-g",
"--genomes",
dest="genomes",
type="string",
help="genomes to analyse.")
parser.add_option("-i",
"--priority",
dest="priority",
type="string",
help="quality priority.")
parser.add_option("-s",
"--sort",
dest="sort",
type="string",
help="sort order.")
parser.add_option("-p",
"--peptides",
dest="filename_peptides",
type="string",
help="filename with template peptide sequences.")
parser.add_option("-m",
"--methods",
dest="methods",
type="string",
help="methods to apply [missed].")
parser.add_option(
"-f",
"--filter",
dest="filename_filter",
type="string",
help=
"filename with schema|prediction_id|gene to use as filter. The prediction_ids are used for filtering."
)
parser.add_option("-q",
"--filter-quality",
dest="filter_quality",
type="string",
help="only consider predictions of given qualities.")
parser.add_option("--pattern-output",
dest="pattern_output",
type="string",
help="output pattern for multiple file output.")
parser.add_option("--pattern-stats",
dest="pattern_stats",
type="string",
help="output pattern for multiple statistics output.")
parser.add_option("--outfile-clusters",
dest="outfile_clusters",
type="string",
help="output filename for clusters.")
parser.add_option("--infile-clusters",
dest="infile_clusters",
type="string",
help="input filename for clusters.")
parser.add_option("-n",
"--non-redundant",
dest="non_redundant",
action="store_true",
help="use non-redundant set for output.")
parser.add_option("--clustering-method",
dest="clustering_method",
type="choice",
choices=("fragment", "hid"),
help="clustering method to use.")
parser.set_defaults(
genomes="",
priority="CG,PG,SG,RG,CP,PP,SP,RP,CF,PF,SF,UG,UP,UF,BF,UK",
sort="CG,PG,SG,RG,CP,PP,SP,RP,CF,PF,SF,UG,UP,UF,BF,UK",
methods="missed",
peptides=None,
filename_filter=None,
separator="|",
filter_quality=None,
pattern_output="%s",
pattern_stats=None,
clustering_method="fragment",
outfile_clusters=None,
infile_clusters=None,
non_redundant=False,
format_percent="%5.2f",
)
(options, args) = E.Start(parser, add_psql_options=True)
if options.filename_peptides:
peptides = Genomics.ReadPeptideSequences(
open(options.filename_peptides, "r"))
else:
peptides = {}
if options.genomes:
options.genomes = options.genomes.split(",")
if options.priority:
options.priority = options.priority.split(",")
if options.methods:
options.methods = options.methods.split(",")
if options.sort:
options.sort = options.sort.split(",")
if options.filter_quality:
options.filter_quality = options.filter_quality.split(",")
subset = {}
if options.filename_filter:
data = map(
lambda x: x[:-1].split(options.separator)[:3],
filter(lambda x: x[0] != "#",
open(options.filename_filter, "r").readlines()))
for s, p, g in data:
if s not in subset:
subset[s] = {}
subset[s][p] = 1
if len(options.sort) != len(options.priority):
raise "different number of classes in sort order and priority order"
dbhandle = pgdb.connect(options.psql_connection)
# Cluster peptides
if options.infile_clusters:
map_peptide2cluster, map_cluster2peptide = IOTools.ReadMap(
open(options.infile_clusters, "r"), both_directions=True)
elif peptides:
if options.clustering_method == "fragment":
map_cluster2peptide, map_peptide2cluster = ClusterPeptidesByFragment(
peptides)
elif options.clustering_method == "hid":
map_cluster2peptide, map_peptide2cluster = ClusterPeptidesByHid(
peptides)
else:
map_cluster2peptide = {}
map_peptide2cluster = {}
if map_cluster2peptide and options.loglevel >= 1:
options.stdlog.write(
"# clustering of peptides: %i cluster for %i peptides\n" %
(len(map_cluster2peptide), len(map_peptide2cluster)))
sys.stdout.flush()
if options.outfile_clusters and not options.infile_clusters:
options.stdlog.write("# writing clusters to %s\n" %
options.outfile_clusters)
outfile = open(options.outfile_clusters, "w")
for k, v in map_peptide2cluster.items():
outfile.write("%s\t%s\n" % (k, v))
outfile.close()
for method in options.methods:
if method == "stats":
# Count number of missed unique genes/transcripts
headers = (
"species",
"genes",
"found_genes",
"missed_genes",
"pfound_genes",
"pmissed_genes",
"nr_found_genes",
"nr_missed_genes",
"pnr_found_genes",
"pnr_missed_genes",
"transcripts",
"found_transcripts",
"missed_transcripts",
"pfound_transcripts",
"pmissed_transcripts",
"nr_found_transcripts",
"nr_missed_transcripts",
"pnr_found_transcripts",
"pnr_missed_transcripts",
)
options.stdout.write("\t".join(headers) + "\n")
for genome in options.genomes:
r = GetQueryInfo(dbhandle, genome, options, subset)
found_genes, genes, found_transcripts, transcripts =\
CountFoundGenes(map(lambda x: (x[0], x[1], x[2]), r),
map_peptide2cluster)
nrfound_genes, nrgenes, nrfound_transcripts, nrtranscripts =\
CountFoundGenes(map(lambda x: (x[0], x[1], x[3]), r),
map_peptide2cluster)
nfound_genes = len(found_genes)
nfound_transcripts = len(found_transcripts)
nnrfound_genes = len(nrfound_genes)
nnrfound_transcripts = len(nrfound_transcripts)
ngenes = len(genes)
ntranscripts = len(transcripts)
if ngenes == 0 or ntranscripts == 0:
continue
f1 = lambda x: 100 * float(x) / ngenes
f2 = lambda x: 100 * float(x) / ntranscripts
options.stdout.write(
"%s\t%i\t%i\t%i\t%5.2f\t%5.2f\t%i\t%i\t%5.2f\t%5.2f\t%i\t%i\t%i\t%5.2f\t%5.2f\t%i\t%i\t%5.2f\t%5.2f\n"
%
(genome, ngenes, nfound_genes, ngenes - nfound_genes,
f1(nfound_genes), f1(ngenes - nfound_genes),
nnrfound_genes, ngenes - nnrfound_genes,
f1(nnrfound_genes), f1(ngenes - nnrfound_genes),
ntranscripts, nfound_transcripts,
ntranscripts - nfound_transcripts, f2(nfound_transcripts),
f2(ntranscripts - nfound_transcripts),
nnrfound_transcripts, ntranscripts - nnrfound_transcripts,
f2(nnrfound_transcripts),
f2(ntranscripts - nnrfound_transcripts)))
elif method == "missed":
headers = (
"species",
"genes",
"transcripts",
"missed_genes",
"missed_transcripts",
"percent_missed_genes",
"percent_missed_transcripts",
)
options.stdout.write("\t".join(headers) + "\n")
all_missed_genes = {}
all_missed_transcripts = {}
for genome in options.genomes:
r = GetQueryInfo(dbhandle, genome, options, subset)
if options.non_redundant:
found_genes, genes, found_transcripts, transcripts =\
CountFoundGenes(map(lambda x: (x[0], x[1], x[3]), r),
map_peptide2cluster)
else:
found_genes, genes, found_transcripts, transcripts =\
CountFoundGenes(map(lambda x: (x[0], x[1], x[2]), r),
map_peptide2cluster)
sg = set(genes)
missed_genes = sg.difference(found_genes)
for x in missed_genes:
if x not in all_missed_genes:
all_missed_genes[x] = []
all_missed_genes[x].append(genome)
sm = set(transcripts)
missed_transcripts = sm.difference(found_transcripts)
for x in missed_transcripts:
if x not in all_missed_transcripts:
all_missed_transcripts[x] = []
all_missed_transcripts[x].append(genome)
options.stdout.write(
"%s\t%i\t%i\t%i\t%i\t%s\t%s\n" %
(genome, len(genes), len(transcripts), len(missed_genes),
len(missed_transcripts), options.format_percent %
(100.0 * float(len(missed_genes)) / len(genes)),
options.format_percent %
(100.0 * float(len(missed_transcripts)) /
len(transcripts))))
for section in ("genes", "transcripts"):
if section == "genes":
missed = all_missed_genes
else:
missed = all_missed_transcripts
writeListMissed(open(options.pattern_output % section, "w"),
missed, options.genomes, options)
if options.pattern_stats:
outfile = open(options.pattern_stats % section, "w")
else:
outfile = options.stdout
outfile.write("# statistics for %s\n" % section)
writeStatsMissed(outfile, missed, options.genomes, options)
if outfile != options.stdout:
outfile.close()
E.Stop()
url=None,
radius_increment=40,
min_contig_size=10000,
remove_empty_contigs=True,
separator="|",
quality2symbol={'CG': "circle", 'PG': "circle", 'SG': "circle"},
quality2mask=(
"RG", "CP", "PP", "SP", "RP", "CF", "PF", "SF", "UG", "UP", "UF", "BF", "UK"),
sort_by_size = True,
input_format = "pairwise",
)
(options, args) = Experiment.Start(parser, add_pipe_options=True)
if options.filename_contig_sizes:
map_contig2size = IOTools.ReadMap(open(options.filename_contig_sizes, "r"),
map_functions=(str, int))
# read data and get contigs that are used (i.e.: remove empty contigs)
chrs = {}
lines = sys.stdin.readlines()
if options.remove_empty_contigs:
for line in lines:
if line[0] == "#":
continue
d = line[:-1].split("\t")
cluster_id, in_locations, in_tree = d[:3]
for l in in_locations.split(";"):
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: mali2predictions.py 2781 2009-09-10 11:33:14Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-g",
"--genome-file",
dest="genome_file",
type="string",
help="filename with genome.")
parser.add_option("-l",
"--filename-locations",
dest="filename_locations",
type="string",
help="filename with locations")
parser.add_option("-m",
"--master",
dest="master",
type="string",
help="the master determines the frame.")
parser.set_defaults(filename_locations=None, gap_chars="-.", master=None)
(options, args) = E.Start(parser, add_pipe_options=True)
if len(args) > 0:
print USAGE, "no arguments required."
sys.exit(2)
mali = Mali.Mali()
mali.readFromFile(sys.stdin)
identifiers = mali.getIdentifiers()
aligned_columns, aligned_exons = getAlignedColumns(mali, options)
map_id2location = {}
if options.filename_locations:
map_id2location = IOTools.ReadMap(open(options.filename_locations,
"r"))
options.stdout.write(Prediction.Prediction().getHeader() + "\n")
nid = 1
for identifier in identifiers:
if options.loglevel >= 2:
options.stdlog.write("# processing %s\n" % (identifier))
entry = mali.getEntry(identifier)
sequence = entry.mString
if sequence[0] not in string.lowercase:
raise "all sequences should start with an exon."
was_exon = True
d = 0
alignment = []
carry_over = 0
last_codon = []
codon = []
nchars_in_codon = 0
n = 0
last_master_residue = 0
master_residue = 0
for column in range(len(sequence)):
c = sequence[column]
is_gap = c in options.gap_chars
is_aligned = column in aligned_columns
is_exon = column in aligned_exons
if is_gap:
continue
if is_exon:
master_residue = aligned_exons[column]
codon.append((n, master_residue))
n += 1
# check if we have a complete codon
if is_exon:
# A codon is complete, if it ends at frame 2 or
# it spans more than one codons in the master.
# Gaps in the master that are a multiple of 3 are ignored
d = master_residue - last_master_residue - 1
if master_residue % 3 == 2 or (d % 3 != 0 and d > 0):
if last_codon:
d = codon[0][0] - last_codon[-1][0] - 1
if d > 0:
# add in-frame introns
if d > 10:
alignment.append(["5", 0, 2])
alignment.append(["I", 0, d - 4])
alignment.append(["3", 0, 2])
else:
raise "untreated case"
alignment += processCodon(codon)
last_codon = codon
codon = []
last_master_residue = master_residue
last = alignment[0]
new_alignment = []
for this in alignment[1:]:
if this[0] == last[0]:
last[1] += this[1]
last[2] += this[2]
continue
new_alignment.append(last)
last = this
new_alignment.append(last)
if options.loglevel >= 4:
options.stdlog.write("# output=%s\n" % (str(new_alignment)))
assert (new_alignment[-1][2] % 3 == 0)
lalignment = sum(map(lambda x: x[2], new_alignment))
prediction = Prediction.Prediction()
prediction.mQueryToken = identifier
genomic_sequence = re.sub("[%s]" % options.gap_chars, "",
mali[identifier])
prediction.mPredictionId = nid
nid += 1
if identifier in map_id2location:
prediction.mSbjctToken, prediction.mSbjctStrand, sfrom, sto = map_id2location[
identifier].split(":")[:4]
prediction.mSbjctGenomeFrom = int(sfrom) + entry.mFrom
prediction.mSbjctGenomeTo = int(sto)
else:
prediction.mSbjctToken = "unk"
prediction.mSbjctStrand = "+"
prediction.mSbjctGenomeFrom = 0
prediction.mQueryCoverage = 100
prediction.mPercentIdentity = 100
prediction.mPercentSimilarity = 100
prediction.mQueryLength = prediction.mQueryTo
prediction.mSbjctGenomeTo = prediction.mSbjctGenomeFrom + lalignment
prediction.mMapPeptide2Genome = new_alignment
prediction.mAlignmentString = string.join(
map(lambda x: string.join(map(str, x), " "),
prediction.mMapPeptide2Genome), " ")
prediction.mMapPeptide2Translation, prediction.mTranslation = Genomics.Alignment2PeptideAlignment(
prediction.mMapPeptide2Genome, 0, 0, genomic_sequence)
(prediction.mNIntrons, prediction.mNFrameShifts, prediction.mNGaps, prediction.mNSplits, prediction.mNStopCodons, disruptions) = \
Genomics.CountGeneFeatures(0,
prediction.mMapPeptide2Genome,
genomic_sequence)
options.stdout.write(str(prediction) + "\n")
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv: argv = sys.argv
# setup command line parser
parser = E.OptionParser(
version=
"%prog version: $Id: cgat_script_template.py 2871 2010-03-03 10:20:44Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-t",
"--template-bam",
dest="filename_genome_bam",
type="string",
help="input bam file for header information [%default]")
parser.add_option("-s",
"--contig-sizes",
dest="filename_contigs",
type="string",
help="filename with contig sizes [%default]")
parser.add_option(
"-o",
"--colour",
dest="colour_mismatches",
action="store_true",
help="mismatches will use colour differences (CM tag) [%default]")
parser.add_option("-i",
"--ignore-mismatches",
dest="ignore_mismatches",
action="store_true",
help="ignore mismatches [%default]")
parser.add_option(
"-c",
"--remove-contigs",
dest="remove_contigs",
type="string",
help="','-separated list of contigs to remove [%default]")
parser.add_option("-f",
"--force",
dest="force",
action="store_true",
help="force overwriting of existing files [%default]")
parser.add_option("-u",
"--unique",
dest="unique",
action="store_true",
help="remove reads not matching uniquely [%default]")
parser.set_defaults(
filename_genome_bam=None,
filename_gtf=None,
filename_mismapped=None,
remove_contigs=None,
force=False,
unique=False,
colour_mismatches=False,
ignore_mismatches=False,
)
## add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
genomefile, referencenames, referencelengths = None, None, None
if options.filename_genome_bam:
genomefile = pysam.Samfile(options.filename_genome_bam, "rb")
elif options.filename_contigs:
contigs = IOTools.ReadMap(IOTools.openFile(options.filename_contigs))
data = zip(*list(contigs.iteritems()))
referencenames, referencelengths = data[0], map(int, data[1])
else:
raise ValueError(
"please provide either --template-bam or --contig-sizes")
infile = pysam.Samfile("-", "rb")
outfile = pysam.Samfile("-",
"wb",
template=genomefile,
referencenames=referencenames,
referencelengths=referencelengths)
if options.colour_mismatches:
tag = "CM"
else:
tag = "NM"
nambiguous = 0
ninput = 0
nunmapped = 0
ncigar = 0
nfull = 0
noutput = 0
contig2tid = dict([(y, x) for x, y in enumerate(outfile.references)])
for qname, readgroup in itertools.groupby(infile, lambda x: x.qname):
ninput += 1
reads = list(readgroup)
if reads[0].is_unmapped:
nunmapped += 1
continue
# filter for best match
best = min([x.opt(tag) for x in reads])
reads = [x for x in reads if x.opt(tag) == best]
if len(reads) > 1:
nambiguous += 1
continue
read = reads[0]
# reject complicated matches (indels, etc)
# to simplify calculations below.
if len(read.cigar) > 1:
ncigar += 1
continue
# set NH flag to latest count
t = dict(read.tags)
t['NH'] = 1
read.tags = list(t.iteritems())
sname = infile.getrname(read.tid)
contig, first_exon_start, middle, last_exon_end, splice, strand = sname.split(
"|")
first_exon_end, last_exon_start = middle.split("-")
first_exon_start, first_exon_end, last_exon_start, last_exon_end = map(int, (\
first_exon_start, first_exon_end, last_exon_start, last_exon_end ) )
first_exon_end += 1
total = first_exon_end - first_exon_start + last_exon_end - last_exon_start
first_exon_length = first_exon_end - first_exon_start
match1 = first_exon_length - read.pos
intron_length = last_exon_start - first_exon_end
match2 = read.qlen - match1
# match lies fully in one exon - ignore
if match1 <= 0 or match2 <= 0:
nfull += 1
continue
# increment pos
read.pos = first_exon_start + read.pos
read.tid = contig2tid[contig]
# 3 = BAM_CREF_SKIP
read.cigar = [(0, match1), (3, intron_length), (0, match2)]
outfile.write(read)
noutput += 1
outfile.close()
if genomefile:
genomefile.close()
c = E.Counter()
c.input = ninput
c.output = noutput
c.full = nfull
c.cigar = ncigar
c.ambiguous = nambiguous
c.unmapped = nunmapped
E.info("%s" % str(c))
## write footer and output benchmark information.
E.Stop()
parser.add_option("--dump", dest="dump", action="store_true",
help="dump output.")
parser.set_defaults(
separator="|",
dump=False,
filename_map=None,
filename_alignment="-",
filename_tree=None,
)
(options, args) = E.Start(parser)
if options.filename_map:
map_species2sp = IOTools.ReadMap(open(options.filename_map, "r"))
E.debug("species map: %s" % str(map_species2sp))
identifier_parser = IdentifierParserGPipe(map_species2sp=map_species2sp)
njtree = NJTree(identifier_parser=identifier_parser)
njtree.SetLog(options.stdlog)
njtree.SetErr(options.stderr)
if options.filename_tree:
njtree.SetSpeciesTree(options.filename_tree)
mali = Mali.Mali()
if options.filename_alignment == "-":
def main(argv=None):
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option(
"-w",
"--filename-weights",
dest="filename_weights",
type="string",
help=
"filename with codon frequencies. Multiple filenames can be separated by comma [default=%default]."
)
parser.add_option("-s",
"--sections",
dest="sections",
type="choice",
action="append",
choices=("length", "hid", "na", "aa", "degeneracy",
"bias", "codons", "codon-usage",
"codon-translator"),
help="which sections to output [default=%default]")
parser.add_option(
"-t",
"--type",
dest="seqtype",
type="choice",
choices=("na", "aa"),
help=
"type of sequence: na=nucleotides, aa=amino acids [default=%default].")
parser.add_option(
"-e",
"--regex-identifier",
dest="regex_identifier",
type="string",
help=
"regular expression to extract identifier from fasta description line [default=%default]."
)
parser.set_defaults(
filename_weights="uniform",
pseudocounts=1,
sections=[],
regex_identifier="(.+)",
seqtype="na",
)
(options, args) = E.Start(parser, argv=argv)
options.filename_weights = options.filename_weights.split(",")
rx = re.compile(options.regex_identifier)
reference_codons = []
if options.filename_weights:
for filename in options.filename_weights:
if filename == "uniform":
reference_codons.append(Genomics.GetUniformCodonUsage())
else:
reference_codons.append(
IOTools.ReadMap(open(filename, "r"),
has_header=True,
map_functions=(str, float)))
## print codon table differences
E.info("difference between supplied codon usage preferences.")
for x in range(0, len(reference_codons)):
for y in range(0, len(reference_codons)):
if x == y: continue
# calculate KL distance
a = reference_codons[x]
b = reference_codons[y]
d = 0
for codon, p in a.items():
if Genomics.IsStopCodon(codon): continue
d += b[codon] * math.log(b[codon] / p)
E.info("tablediff\t%s\t%s\t%f" %
(options.filename_weights[x],
options.filename_weights[y], d))
iterator = FastaIterator.FastaIterator(options.stdin)
def getCounter(section):
if options.seqtype == "na":
if section == "length":
s = SequencePropertiesLength()
elif section == "hid":
s = SequencePropertiesHid()
elif section == "na":
s = SequencePropertiesNA()
elif section == "aa":
s = SequencePropertiesAA()
elif section == "degeneracy":
s = SequencePropertiesDegeneracy()
elif section == "bias":
s = SequencePropertiesBias(reference_codons)
elif section == "codons":
s = SequencePropertiesCodons()
elif section == "codon-usage":
s = SequencePropertiesCodonUsage()
elif section == "codon-translator":
s = SequencePropertiesCodonTranslator()
else:
raise ValueError("unknown section %s" % section)
elif options.seqtype == "aa":
if section == "length":
s = SequencePropertiesLength()
elif section == "hid":
s = SequencePropertiesHid()
elif section == "aa":
s = SequencePropertiesAminoAcids()
else:
raise ValueError("unknown section %s" % section)
return s
## setup totals
totals = {}
for section in options.sections:
totals[section] = getCounter(section)
options.stdout.write("id")
for section in options.sections:
options.stdout.write("\t" + "\t".join(totals[section].getHeaders()))
options.stdout.write("\n")
options.stdout.flush()
for cur_record in iterator:
sequence = re.sub(" ", "", cur_record.sequence).upper()
if len(sequence) == 0:
E.warning("empty sequence %s" % cur_record.title)
continue
id = rx.search(cur_record.title).groups()[0]
options.stdout.write("%s" % id)
options.stdout.flush()
for section in options.sections:
s = getCounter(section)
s.loadSequence(sequence)
totals[section].addProperties(s)
options.stdout.write("\t" + "\t".join(s.getFields()))
options.stdout.write("\n")
options.stdout.write("total")
for section in options.sections:
options.stdout.write("\t" + "\t".join(totals[section].getFields()))
options.stdout.write("\n")
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version: $Id: matrix2stats.py 2795 2009-09-16 15:29:23Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-m", "--method", dest="method", type="choice",
choices=("chi-squared", "pearson-chi-squared"),
help="statistical methods to apply.")
parser.add_option("-t", "--header-names", dest="headers", action="store_true",
help="matrix has row/column headers.")
parser.add_option("--no-headers", dest="headers", action="store_false",
help="matrix has no row/column headers.")
parser.add_option("-i", "--input-format", dest="input_format", type="choice",
choices=("full", "sparse", "phylip"),
help="""input format for matrix.""" )
parser.add_option("-o", "--output-format", dest="output_format", type="choice",
choices=("full", "sparse", "phylip"),
help="""output format for matrix.""" )
parser.add_option("-p", "--parameters", dest="parameters", action="append", type="string",
help="parameters for various functions.")
parser.add_option("-a", "--iteration", dest="iteration", type="choice",
choices=("pairwise", "all-vs-all"),
help="""how to compute stats [%default].""" )
parser.set_defaults(
method="chi-squared",
headers=True,
value_format="%6.4f",
pvalue_format="%6.4e",
input_format="full",
write_separators=True,
parameters=[],
iteration=None,
)
(options, args) = E.Start(parser)
lines = [x for x in sys.stdin.readlines() if x[0] != "#"]
chunks = [x for x in range(len(lines)) if lines[x][0] == ">"]
if not chunks:
options.write_separators = False
chunks = [-1]
chunks.append(len(lines))
ninput, noutput, nskipped = 0, 0, 0
if options.write_separators:
options.stdout.write("test\t")
header_prefix = ""
if options.method == "chi-squared":
header_prefix = "observed\texpected"
options.stdout.write("\t".join(
(header_prefix, "n", "min", "max", "chi", "df", "P", "passed", "phi")) + "\n")
elif options.method in ("pearson-chi-squared",):
options.stdout.write("column\t")
options.stdout.write("\t".join(
(header_prefix, "n", "prob", "obs", "exp", "chi", "df", "P", "passed", "phi")) + "\n")
if len(options.parameters) == 0:
raise "out of parameters - please supply probability or filename with probabilities."
param = options.parameters[0]
del options.parameters[0]
if options.write_separators:
probabilities = IOTools.ReadMap(
IOTools.openFile(param, "r"), map_functions=(str, float))
else:
probability = float(param)
for x in range(len(chunks) - 1):
ninput += 1
matrix, row_headers, col_headers = MatlabTools.readMatrix(
StringIO("".join(lines[chunks[x] + 1:chunks[x + 1]])),
format=options.input_format,
headers=options.headers)
nrows, ncols = matrix.shape
if options.loglevel >= 2:
options.stdlog.write("# read matrix: %i x %i, %i row titles, %i colum titles.\n" %
(nrows, ncols, len(row_headers), len(col_headers)))
if options.write_separators:
options.stdout.write(lines[chunks[x]][1:-1] + "\t")
pairs = []
if options.iteration == "pairwise":
pairs = []
for row1 in range(0, len(row_headers)):
for row2 in range(row1 + 1, len(row_headers)):
pairs.append((row1, row2))
elif options.iteration == "all-vs-all":
pairs = []
for row1 in range(0, len(row_headers)):
for row2 in range(0, len(row_headers)):
if row1 == row2:
continue
pairs.append((row1, row2))
if options.method == "chi-squared":
for row1, row2 in pairs:
row_header1 = row_headers[row1]
row_header2 = row_headers[row2]
try:
result = Stats.doChiSquaredTest(
numpy.vstack((matrix[row1], matrix[row2])))
except ValueError:
nskipped += 1
continue
noutput += 1
options.stdout.write("\t".join((
"%s" % row_header1,
"%s" % row_header2,
"%i" % result.mSampleSize,
"%i" % min(matrix.flat),
"%i" % max(matrix.flat),
options.value_format % result.mChiSquaredValue,
"%i" % result.mDegreesFreedom,
options.pvalue_format % result.mProbability,
"%s" % result.mSignificance,
options.value_format % result.mPhi)) + "\n")
elif options.method == "pearson-chi-squared":
if nrows != 2:
raise ValueError("only implemented for 2xn table")
if options.write_separators:
id = re.match("(\S+)", lines[chunks[x]][1:-1]).groups()[0]
probability = probabilities[id]
for col in range(ncols):
options.stdout.write("%s\t" % col_headers[col])
result = Stats.doPearsonChiSquaredTest(
probability, sum(matrix[:, col]), matrix[0, col])
options.stdout.write("\t".join((
"%i" % result.mSampleSize,
"%f" % probability,
"%i" % result.mObserved,
"%f" % result.mExpected,
options.value_format % result.mChiSquaredValue,
"%i" % result.mDegreesFreedom,
options.pvalue_format % result.mProbability,
"%s" % result.mSignificance,
options.value_format % result.mPhi)))
if col < ncols - 1:
options.stdout.write("\n")
if options.write_separators:
options.stdout.write(lines[chunks[x]][1:-1] + "\t")
options.stdout.write("\n")
E.info("# ninput=%i, noutput=%i, nskipped=%i\n" %
(ninput, noutput, nskipped))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version: $Id: tree_strain2species.py 2782 2009-09-10 11:40:29Z andreas $",
usage=globals()["__doc__"])
parser.add_option("--filename-synonyms", dest="filename_synonyms", type="string",
help="filename with synonyms. Use this to aggregate several strains for a species.")
parser.add_option("--filename-genes", dest="output_filename_genes", type="string",
help="output filename with new gene names.")
parser.add_option("--species-tree", dest="species_tree", action="store_true",
help="input tree are species trees. If not given, the trees are assumed to be gene trees.")
parser.add_option("--merge-mode", dest="merge_mode", type="choice",
choices=("ignore", "add-mean", "add-max", "add-min"),
help="how to deal with branch lengths of merged nodes.")
parser.set_defaults(
filename_synonyms="map_strain2species",
pattern_gene="J%06i",
output_format="nh",
separator="|",
output_filename_genes=None,
keep_old_names=False,
species_tree=False,
merge_mode="ignore",
)
(options, args) = E.Start(parser, add_pipe_options=True)
########################################################################
########################################################################
########################################################################
# read synonyms
if options.filename_synonyms:
infile = open(options.filename_synonyms, "r")
map_strain2species = IOTools.ReadMap(infile)
infile.close()
else:
map_strain2species = {}
lines = map(lambda x: x[:-1], sys.stdin.readlines())
ninput, noutput, nskipped, nmerged = 0, 0, 0, 0
# iterate over chunks
chunks = filter(lambda x: lines[x][0] == ">", range(len(lines)))
if len(chunks) == 0:
chunks = [0]
chunks.append(len(lines))
if options.species_tree:
processSpeciesTrees(chunks, lines, map_strain2species, options)
else:
processGeneTrees(chunks, lines, map_strain2species, options)
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: optic/plot_duplications.py 2782 2009-09-10 11:40:29Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-e",
"--headers",
dest="headers",
action="store_true",
help="first row is a header [ignored].")
parser.add_option("-t",
"--title",
dest="title",
type="string",
help="page title.")
parser.add_option("-f",
"--footer",
dest="footer",
type="string",
help="page footer.")
parser.add_option("-c",
"--contig-sizes",
dest="filename_contig_sizes",
type="string",
help="filname with contig sizes.")
parser.add_option("-r",
"--radius",
dest="radius",
type="int",
help="radius.")
parser.add_option("-i",
"--increment",
dest="radius_increment",
type="int",
help="radius increment.")
parser.add_option("-u",
"--url",
dest="url",
type="string",
help="string to build url for annotation.")
parser.add_option("--min-contig",
dest="min_contig_size",
type="string",
help="minimum contig size to delineate.")
parser.add_option("--min-value",
dest="min_value",
type="float",
help="minimum branch length.")
parser.add_option("--max-value",
dest="max_value",
type="float",
help="maximum branch length.")
parser.set_defaults(
filename_contig_sizes=None,
headers=False,
titles="",
pattern_filename=None,
title="",
footer="",
radius=3000,
min_value=0.0,
max_value=0.2,
url=None,
radius_increment=40,
min_contig_size=10000,
remove_empty_contigs=True,
separator="|",
quality2symbol={
'CG': "circle",
'PG': "circle",
'SG': "circle"
},
quality2mask=("RG", "CP", "PP", "SP", "RP", "CF", "PF", "SF", "UG",
"UP", "UF", "BF", "UK"),
sort_by_size=True,
input_format="pairwise",
)
(options, args) = E.Start(parser, add_pipe_options=True)
if options.filename_contig_sizes:
map_contig2size = IOTools.ReadMap(open(options.filename_contig_sizes,
"r"),
map_functions=(str, int))
# read data and get contigs that are used (i.e.: remove empty contigs)
chrs = {}
lines = sys.stdin.readlines()
if options.remove_empty_contigs:
for line in lines:
if line[0] == "#":
continue
d = line[:-1].split("\t")
cluster_id, in_locations, in_tree = d[:3]
for l in in_locations.split(";"):
gene_id, chr, strand, sbjct_from, sbjct_to = l.split(":")
if chr not in map_contig2size:
continue
chrs[chr] = 1
for k in map_contig2size.keys():
if k not in chrs:
del map_contig2size[k]
k = map_contig2size.keys()
if len(k) == 0:
E.Stop()
sys.exit(0)
k.sort()
if options.sort_by_size:
k.sort(lambda x, y: cmp(map_contig2size[x], map_contig2size[y]))
plot = DuplicationPlot(k, map_contig2size, num_entries=0)
plot.mRadiusIncrement = options.radius_increment
plot.mRadius = options.radius
plot.mMaxValue = options.max_value
plot.mMinValue = options.min_value
if options.title:
plot.setTitle(options.title)
if options.footer:
plot.setFooter(options.footer)
plot.initializePlot()
data = []
if options.input_format == "pairwise":
# read data from pairwise analysis
# format is: cluster_id, locations of duplications, tree of
# duplications
for line in lines:
if line[0] == "#":
continue
d = line[:-1].split("\t")
cluster_id, in_locations, in_tree = d[:3]
mi, ma = 0, 0
found = False
n = 0
chrs = {}
for l in in_locations.split(";"):
gene_id, chr, strand, sbjct_from, sbjct_to = l.split(":")
if chr not in map_contig2size:
continue
chrs[chr] = 1
sbjct_from, sbjct_to = int(sbjct_from), int(sbjct_to)
xi = plot.getPosition(chr, strand, sbjct_from)
xa = plot.getPosition(chr, strand, sbjct_to)
if not mi:
mi = xi
else:
mi = min(mi, xi)
n += 1
ma = max(ma, xa)
found = True
if not found:
continue
cis = len(chrs) == 1
if options.loglevel >= 2:
options.stdlog.write(
"# adding duplications in cluster %s: %s with tree %s\n" %
(cluster_id, in_locations, in_tree))
data.append((cis, n, mi, ma, cluster_id, in_locations, in_tree))
data.sort()
plot.mNumEntries = len(data)
plot.initializePlot()
last_ndups = 0
for cis, ndups, mi, ma, cluster_id, in_locations, in_tree in data[:]:
if ndups != last_ndups:
plot.pushRadius()
plot.addSeparator()
last_ndups = ndups
map_gene2location = {}
for l in in_locations.split(";"):
gene_id, chr, strand, sbjct_from, sbjct_to = l.split(":")
if chr not in map_contig2size:
continue
sbjct_from, sbjct_to = int(sbjct_from), int(sbjct_to)
map_gene2location[gene_id] = (chr, strand, sbjct_from, sbjct_to)
if not map_gene2location:
continue
tree = TreeTools.Newick2Tree(in_tree)
# the last subset is all nodes again.
s = TreeTools.GetSubsets(tree)
is_first = True
for children, height, branchlength in s[:-1]:
if len(children) == 1:
continue
c = map(lambda x: x.split(options.separator), children)
plot.addDuplication(c,
map_gene2location,
height,
url=options.url,
with_separator=is_first,
link_to_previous=not is_first,
quality2symbol=options.quality2symbol,
quality2mask=options.quality2mask)
is_first = False
plot.writeToFile(sys.stdout)
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: r_compare_distributions.py 2782 2009-09-10 11:40:29Z andreas $"
)
parser.add_option(
"-m",
"--method",
dest="method",
type="choice",
help=
"method to use: ks=Kolmogorov-Smirnov, mwu=Mann-WhitneyU, shapiro=Shapiro-Wilk, paired-mwu=paired Mann-WhitneyU, paired-t=paired t-test [default=%default]",
choices=("ks", "mwu", "shapiro", "paired-mwu", "paired-t"))
parser.add_option("-a",
"--hardcopy",
dest="hardcopy",
type="string",
help="write hardcopy to file.",
metavar="FILE")
parser.add_option("-1",
"--infile1",
dest="filename_input1",
type="string",
help="input filename for distribution 1.")
parser.add_option("-2",
"--infile2",
dest="filename_input2",
type="string",
help="input filename for distribution 2.")
parser.add_option("--plot-legend",
dest="legend",
type="string",
help="legend for histograms."
"")
parser.add_option("-f",
"--infile-map",
dest="filename_input_map",
type="string",
help="input filename for mapping categories to values.")
parser.add_option(
"-n",
"--norm-test",
dest="norm_test",
action="store_true",
help=
"""test if a set of values is normally distributed. Mean and variance
are calculated from the data.""")
parser.add_option("-b",
"--num-bins",
dest="num_bins",
type="int",
help="""number of bins (for plotting purposes only).""")
parser.add_option("--bin-size",
dest="bin_size",
type="float",
help="""bin size for plot.""")
parser.add_option("--min-value",
dest="min_value",
type="float",
help="""minimum_value for plot.""")
parser.add_option("--max-value",
dest="max_value",
type="float",
help="""maximum_value for plot.""")
parser.add_option("--skip-plot",
dest="plot",
action="store_false",
help="""skipping plotting.""")
parser.add_option("--header-names",
dest="header",
type="string",
help="""header of value column [default=%default].""")
parser.add_option("--title",
dest="title",
type="string",
help="""plot title [default=%default].""")
parser.set_defaults(
method="ks",
filename_input1=None,
filename_input2=None,
filename_input_map=None,
legend=None,
norm_test=False,
num_bins=0,
legend_range="2,2",
bin_size=None,
min_value=None,
plot=True,
header="value",
title=None,
)
(options, args) = E.Start(parser, add_pipe_options=True)
kwargs = {}
xargs = []
for arg in args:
if "=" in arg:
key, value = arg.split("=")
kwargs[key] = value
else:
xargs.append(arg)
if options.legend:
options.legend = options.legend.split(",")
map_category2value = {}
if options.filename_input_map:
map_category2value = IOTools.ReadMap(open(options.filename_input_map,
"r"),
map_functions=(str, float))
f = str
else:
f = float
if options.filename_input1:
infile1 = IOTools.openFile(options.filename_input1, "r")
else:
infile1 = sys.stdin
values1, errors1 = IOTools.ReadList(infile1,
map_function=f,
map_category=map_category2value)
if options.filename_input1:
infile1.close()
if errors1 and options.loglevel >= 3:
options.stdlog.write("# errors in input1: %s\n" %
";".join(map(str, errors1)))
if options.norm_test:
mean = R.mean(values1)
stddev = R.sd(values1)
options.stdlog.write(
"# creating %i samples from normal distribution with mean %f and stddev %f\n"
% (len(values1), mean, stddev))
values2 = R.rnorm(len(values1), mean, stddev)
errors2 = ()
else:
values2, errors2 = IOTools.ReadList(open(options.filename_input2, "r"),
map_function=f,
map_category=map_category2value)
if errors2 and options.loglevel >= 3:
options.stdlog.write("# errors in input2: %s\n" %
";".join(map(str, errors2)))
if options.loglevel >= 1:
options.stdlog.write(
"# ninput1=%i, nerrors1=%i, ninput2=%i, nerrors2=%i\n" %
(len(values1), len(errors1), len(values2), len(errors2)))
if options.method in ("paired-mwu", "paired-t"):
if len(values1) != len(values2):
raise ValueError(
"number of values must be equal for paired tests.")
if options.hardcopy:
R.png(options.hardcopy, width=1024, height=768)
if options.method == "ks":
result = R.ks_test(values1, values2, *xargs, **kwargs)
elif options.method == "mwu":
result = R.wilcox_test(values1,
values2,
paired=False,
correct=True,
*xargs,
**kwargs)
elif options.method == "paired-mwu":
result = R.wilcox_test(values1,
values2,
paired=True,
correct=True,
*xargs,
**kwargs)
elif options.method == "paired-t":
result = R.t_test(values1, values2, paired=True, *xargs, **kwargs)
elif options.method == "shapiro":
if len(values1) > 5000:
E.warn(
"shapiro-wilk test only accepts < 5000 values, a random sample has been created."
)
values1 = random.sample(values1, 5000)
result = R.shapiro_test(values1, *xargs, **kwargs)
if options.plot:
R.assign("v1", values1)
R.assign("v2", values2)
if options.title:
# set the size of the outer margins - the title needs to be added at the end
# after plots have been created
R.par(oma=R.c(0, 0, 4, 0))
R.layout(R.matrix((1, 2, 3, 4), 2, 2, byrow=True))
R.boxplot(values1, values2, col=('white', 'red'), main="Boxplot")
R("""qqplot( v1, v2, main ='Quantile-quantile plot' ); lines( c(0,1), c(0,1) );"""
)
# compute breaks:
min_value = min(min(values1), min(values2))
if options.min_value is not None:
min_value = min(min_value, options.min_value)
max_value = max(max(values1), max(values2))
if options.max_value is not None:
max_value = max(max_value, options.max_value)
extra_options = ""
if options.num_bins and not (options.min_value or options.max_value):
extra_options += ", breaks=%i" % options.num_bins
elif options.num_bins and (options.min_value or options.max_value):
bin_size = float((max_value - min_value)) / (options.num_bins + 1)
breaks = [
min_value + x * bin_size for x in range(options.num_bins)
]
extra_options += ", breaks=c(%s)" % ",".join(map(str, breaks))
elif options.bin_size is not None:
num_bins = int(((max_value - min_value) / options.bin_size)) + 1
breaks = [
min_value + x * options.bin_size for x in range(num_bins + 1)
]
extra_options += ", breaks=c(%s)" % ",".join(map(str, breaks))
R("""h1 <- hist( v1, freq=FALSE, density=20, main='Relative frequency histogram' %s)"""
% extra_options)
R("""h2 <- hist( v2, freq=FALSE, add=TRUE, density=20, col='red', offset=0.5, angle=135 %s)"""
% extra_options)
if options.legend:
R("""legend( ( max(c(h1$breaks[-1], h2$breaks[-1])) - min(c(h1$breaks[1], h2$breaks[1]) ) ) / 2,
max( max(h1$density), max(h2$density)) / 2, c('%s'), fill=c('white','red'))"""
% ("','".join(options.legend)))
R("""h1 <- hist( v1, freq=TRUE, density=20, main='Absolute frequency histogram' %s)"""
% extra_options)
R("""h2 <- hist( v2, freq=TRUE, add=TRUE, density=20, col='red', offset=0.5, angle=135 %s )"""
% extra_options)
if options.legend:
R("""legend( ( max(c(h1$breaks[-1], h2$breaks[-1])) - min(c(h1$breaks[1], h2$breaks[1]) ) ) / 2,
max( max(h1$counts), max(h2$counts)) / 2, c('%s'), fill=c('white','red'))"""
% ("','".join(options.legend)))
if options.title:
R.mtext(options.title, 3, outer=True, line=1, cex=1.5)
if options.loglevel >= 1:
options.stdout.write("## Results for %s\n" % result['method'])
options.stdout.write("%s\t%s\n" % ("key", options.header))
for key in list(result.keys()):
if key == "data.name":
continue
options.stdout.write("\t".join((key, str(result[key]))) + "\n")
stat = Stats.Summary(values1)
for key, value in list(stat.items()):
options.stdout.write("%s1\t%s\n" % (str(key), str(value)))
stat = Stats.Summary(values2)
for key, value in list(stat.items()):
options.stdout.write("%s2\t%s\n" % (str(key), str(value)))
if options.plot:
if options.hardcopy:
R.dev_off()
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: fasta2nj.py 2781 2009-09-10 11:33:14Z andreas $")
parser.add_option(
"-m",
"--map",
dest="filename_map",
type="string",
help="filename with mapping of species ids to swissprot species ids.")
parser.set_defaults(
separator="|",
filename_map=None,
)
(options, args) = E.Start(parser)
if options.filename_map:
map_species2sp = IOTools.ReadMap(open(options.filename_map, "r"))
ninput, noutput, nerrors = 0, 0, 0
for line in sys.stdin:
if line[0] == ">":
ninput += 1
id = re.match(">([^/ \t]+)", line[:-1]).groups()[0]
data = id.split(options.separator)
species = data[0]
if len(data) == 2:
gene = data[1]
transcript = None
elif len(data) >= 3:
gene = data[2]
transcript = data[1]
if map_species2sp:
try:
species = map_species2sp[species]
except IndexError:
nerrors += 1
if options.loglevel >= 1:
options.stdlog.write("# could not map species %s\n" %
species)
if transcript:
options.stdout.write(">%s_%s GENEID=%s\n" %
(transcript, species, gene))
else:
options.stdout.write(">%s_%s\n" % (species, gene))
noutput += 1
else:
options.stdout.write(line)
if options.loglevel >= 1:
options.stdlog.write("# ninput=%i, noutput=%i, nerrors=%i\n" %
(ninput, noutput, nerrors))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: r_mann_whitney_u.py 2782 2009-09-10 11:40:29Z andreas $"
)
parser.add_option(
"-m",
"--method",
dest="method",
type="string",
help="method to use [ks=Kolmogorov-Smirnov,mwu=Mann-WhitneyU]")
parser.add_option("-a",
"--hardcopy",
dest="hardcopy",
type="string",
help="write hardcopy to file.",
metavar="FILE")
parser.add_option("-1",
"--infile1",
dest="filename_input1",
type="string",
help="input filename for distribution 1.")
parser.add_option("-2",
"--infile2",
dest="filename_input2",
type="string",
help="input filename for distribution 2.")
parser.add_option("-p",
"--infile-map",
dest="filename_input_map",
type="string",
help="input filename for mapping categories to values.")
parser.set_defaults(
method="ks",
filename_input1=None,
filename_input2=None,
filename_input_map=None,
)
(options, args) = E.Start(
parser,
add_pipe_options=True,
add_psql_options=True,
)
map_category2value = {}
if options.filename_input_map:
map_category2value = IOTools.ReadMap(open(options.filename_input_map,
"r"),
map_functions=(str, float))
values1, errors1 = IOTools.ReadList(open(options.filename_input1, "r"),
map_category=map_category2value)
values2, errors2 = IOTools.ReadList(open(options.filename_input2, "r"),
map_category=map_category2value)
E.info("ninput1=%i, nerrors1=%i, ninput2=%i, nerrors2=%i" %
(len(values1), len(errors1), len(values2), len(errors2)))
if options.hardcopy:
R.png(options.hardcopy, width=1024, height=768)
if options.method == "ks":
result = R.ks_test(values1, values2)
elif options.method == "mwu":
result = R.wilcox_test(values1, values2, paired=False)
R.assign("v1", values1)
R.assign("v2", values2)
R.layout(R.matrix((1, 2, 3, 4), 2, 2, byrow=True))
R.boxplot(values1, values2, col=('white', 'red'), main="Boxplot")
R("""qqplot( v1, v2, main ='Quantile-quantile plot' ); lines( c(0,1), c(0,1) );"""
)
R("""hist( v1, freq=FALSE, width=0.5, density=10, main='Relative frequency histogram')"""
)
R("""hist( v2, freq=FALSE, add=TRUE, width=0.5, col='red', offset=0.5, density=20, angle=135)"""
)
R("""hist( v1, freq=TRUE, width=0.5, density=10, main='Absolute frequency histogram')"""
)
R("""hist( v2, freq=TRUE, add=TRUE, width=0.5, col='red', offset=0.5, density=20, angle=135)"""
)
print "## Results for %s" % result['method']
for x in ['p.value', 'statistic', 'alternative', 'method']:
print x, result[x]
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: shuffle_fasta.py 2782 2009-09-10 11:40:29Z andreas $"
)
parser.add_option(
"-c",
"--codons",
dest="codons",
action="store_true",
help="make sure that shuffled sequences only contain valid codons.")
parser.add_option("-a",
"--conserve-aminos",
dest="conserve_aminos",
action="store_true",
help="conserve amino acids.")
parser.add_option(
"-b",
"--bias",
dest="bias",
type="float",
help=
"introduce bias into codon usage choice. Complete bias is 1.0, while no bias is 0.0."
)
parser.add_option(
"-i",
"--biased-codon-usage",
dest="filename_biased_codon_usage",
type="string",
help="Filename with reference codon usage table for biased codon usage."
)
parser.add_option(
"-u",
"--bulk-codon-usage",
dest="filename_bulk_codon_usage",
type="string",
help=
"Filename with reference codon usage table for unbiased codon usage.")
parser.set_defaults(
codons=False,
conserve_aminos=False,
bias=0.0,
filename_biased_codon_usage=None,
filename_bulk_codon_usage=None,
stop_codons=("TAG", "TAA", "TGA"),
precision=10000,
)
(options, args) = E.Start(parser, add_pipe_options=True)
iterator = FastaIterator.FastaIterator(sys.stdin)
# get map of amino acids to codons
map_aa2codons = Genomics.GetMapAA2Codons()
# for codon based shuffling: build ranges based on strength of bias and on reference codon usage
# Bias switches from completely biased to unbiased. Unbiased is uniform
# usage.
if options.filename_biased_codon_usage:
map_codon2frequency = IOTools.ReadMap(open(
options.filename_biased_codon_usage, "r"),
map_functions=(str, float),
has_header=True)
if options.filename_bulk_codon_usage:
map_codon2frequency_bulk = IOTools.ReadMap(
open(options.filename_bulk_codon_usage, "r"),
map_functions=(str, float),
has_header=True)
codon_ranges = {}
for aa in map_aa2codons.keys():
c = []
x = 0
for codon in map_aa2codons[aa]:
if options.filename_bulk_codon_usage:
u = map_codon2frequency_bulk[codon]
else:
# uniform usage
u = 1.0 / len(map_aa2codons[aa])
g = map_codon2frequency[codon]
f = g + (u - g) * (1.0 - options.bias)
x += f * options.precision
c.append(x)
codon_ranges[aa] = c
while 1:
cur_record = iterator.next()
if cur_record is None:
break
sequence = re.sub(" ", "", cur_record.sequence)
l = len(sequence)
if options.conserve_aminos:
n = []
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
aa = Genomics.MapCodon2AA(codon)
if aa not in map_aa2codons:
continue
if options.bias or options.filename_biased_codon_usage:
# get random number from 0 to precision
v = random.randint(0, options.precision)
# find the corresponding intervall:
l = len(map_aa2codons[aa])
x = 0
while x < l - 1:
if v < codon_ranges[aa][x]:
break
x += 1
else:
x = random.randint(0, len(map_aa2codons[aa]) - 1)
n.append(map_aa2codons[aa][x])
sequence = "".join(n)
else:
sequence = list(sequence)
if options.codons:
while 1:
random.shuffle(sequence)
for codon in [sequence[x:x + 3] for x in range(0, l, 3)]:
if codon in options.stop_codons:
redo = True
break
else:
break
else:
random.shuffle(sequence)
sequence = "".join(sequence)
options.stdout.write(">%s\n%s\n" %
(cur_record.title, "".join(sequence)))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv == None: argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: optic/annotate_clusters.py 2781 2009-09-10 11:33:14Z andreas $"
)
parser.add_option(
"-r",
"--species-regex",
dest="species_regex",
type="string",
help="regular expression to extractspecies from identifier.")
parser.add_option(
"--filename-map",
dest="filename_map_id2cluster",
type="string",
help="filename with mapping information from id to cluster.")
parser.add_option("--filename-interpro",
dest="filename_interpro",
type="string",
help="filename with interpro domain information.")
parser.add_option("--filename-pfam",
dest="filename_pfam",
type="string",
help="filename with pfam domain information.")
parser.set_defaults(
master_species="dmel_vs_dmel4",
separator="|",
filename_map_id2cluster="input.map",
filename_interpro="/home/andreas/projects/flies/data_1v5/interpro.list",
filename_pfam="/home/andreas/projects/flies/data_1v5/pfam.list",
write_no_annotation=True,
separator_fields=";",
)
(options, args) = E.Start(parser,
add_psql_options=True,
add_csv_options=True)
clusters, nerrors = IOTools.ReadList(sys.stdin)
map_id2cluster, map_cluster2id = IOTools.ReadMap(open(
options.filename_map_id2cluster, "r"),
both_directions=True)
if len(clusters) == 0:
clusters = map_cluster2id.keys()
clusters.sort()
if options.filename_interpro:
map_id2interpro = readAnnotationInterpro(
open(options.filename_interpro, "r"))
if options.filename_pfam:
map_id2pfam = readAnnotationPfam(open(options.filename_pfam, "r"))
ninput, noutput, nnomaster, nnoannotation = 0, 0, 0, 0
nskipped = 0
options.stdout.write("cluster\tgenes")
if map_id2interpro:
options.stdout.write("\tinterpro\tidescription")
if map_id2pfam:
options.stdout.write("\tpfam\tpdescription")
options.stdout.write("\n")
for cluster in clusters:
ninput += 1
if cluster not in map_cluster2id:
if options.loglevel >= 1:
options.stdlog.write("# cluster %s not in map.\n" % cluster)
nskipped += 1
continue
genes = set()
for id in map_cluster2id[cluster]:
s, t, g, q = id.split(options.separator)
if s != options.master_species:
continue
genes.add(g)
if not genes:
nnomaster += 1
continue
annotations_interpro = {}
if map_id2interpro:
for gene in genes:
if gene in map_id2interpro:
for annotation in map_id2interpro[gene]:
annotations_interpro[
annotation.mIdentifier] = annotation
annotations_pfam = {}
if map_id2pfam:
for gene in genes:
if gene in map_id2pfam:
for annotation in map_id2pfam[gene]:
annotations_pfam[annotation.mIdentifier] = annotation
nannotations = max(len(annotations_pfam), len(annotations_interpro))
if nannotations == 0 and not options.write_no_annotation:
nnoannotation += 1
continue
options.stdout.write("%s\t%s" % (cluster, ";".join(genes)))
if map_id2interpro:
printAnnotations(options.stdout, annotations_interpro, options)
if map_id2pfam:
printAnnotations(options.stdout, annotations_pfam, options)
options.stdout.write("\n")
noutput += 1
if options.loglevel >= 1:
options.stdlog.write(
"# ninput=%i, noutput=%i, nskipped=%i, nnomaster=%i, nnoannotation=%i\n"
% (ninput, noutput, nskipped, nnomaster, nnoannotation))
E.Stop()
