def runRegexMotifSearch(infiles, outfile):
'''run a regular expression search on sequences.
compute counts.
'''
motif = "[AG]G[GT]T[CG]A"
reverse_motif = "T[GC]A[CA]C[TC]"
controlfile, dbfile = infiles
if not os.path.exists(controlfile):
raise ValueError("control file %s for %s does not exist" %
(controlfile, dbfile))
motifs = []
for x in range(0, 15):
motifs.append(
("DR%i" % x, re.compile(motif + "." * x + motif, re.IGNORECASE)))
for x in range(0, 15):
motifs.append(("ER%i" % x,
re.compile(motif + "." * x + reverse_motif,
re.IGNORECASE)))
db_positions = Motifs.countMotifs(iotools.open_file(dbfile, "r"), motifs)
control_positions = Motifs.countMotifs(iotools.open_file(controlfile, "r"),
motifs)
db_counts, control_counts = Motifs.getCounts(
db_positions), Motifs.getCounts(control_positions)
db_seqcounts, control_seqcounts = Motifs.getOccurances(
db_positions), Motifs.getCounts(control_positions)
ndb, ncontrol = len(db_positions), len(control_positions)
outf = iotools.open_file(outfile, "w")
outf.write(
"motif\tmotifs_db\tmotifs_control\tseq_db\tseq_db_percent\tseq_control\tseq_control_percent\tfold\n"
)
for motif, pattern in motifs:
try:
fold = float(db_seqcounts[motif]) * \
ncontrol / (ndb * control_seqcounts[motif])
except ZeroDivisionError:
fold = 0
outf.write(
"%s\t%i\t%i\t%i\t%s\t%i\t%s\t%5.2f\n" %
(motif, db_counts[motif], control_counts[motif],
db_seqcounts[motif],
iotools.pretty_percent(db_seqcounts[motif],
ndb), control_seqcounts[motif],
iotools.pretty_percent(control_seqcounts[motif], ncontrol), fold))
def __str__(self):
return "\t".join(map(str, (
self.mGenes1, self.mGenes2,
self.mGenesOverlapping1, self.mGenesOverlapping2,
self.mGenesUnique1, self.mGenesUnique2,
self.mExons1, self.mExons2,
self.mExonsOverlapping1, self.mExonsOverlapping2,
self.mExonsUnique1, self.mExonsUnique2,
self.mBases1, self.mBases2,
self.mBasesOverlapping1, self.mBasesOverlapping2,
self.mBasesUnique1, self.mBasesUnique2))) + "\t" +\
"\t".join([iotools.pretty_percent(*x) for x in (
(self.mGenesOverlapping1, self.mGenes1),
(self.mGenesOverlapping2, self.mGenes2),
(self.mGenesUnique1, self.mGenes1),
(self.mGenesUnique2, self.mGenes2),
(self.mExonsOverlapping1, self.mExons1),
(self.mExonsOverlapping2, self.mExons2),
(self.mExonsUnique1, self.mExons1),
(self.mExonsUnique2, self.mExons2),
(self.mBasesOverlapping1, self.mBases1),
(self.mBasesOverlapping2, self.mBases2),
(self.mBasesUnique1, self.mBases1),
(self.mBasesUnique2, self.mBases2))])
def main(argv=None):
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-d",
"--delimiter",
dest="delimiter",
type="string",
help="delimiter to separate columns [%default]")
parser.add_option("-m",
"--method",
dest="methods",
type="choice",
action="append",
choices=["row-describe", "column-describe"],
help="additional methods to apply [%default]")
parser.set_defaults(
delimiter="\t",
methods=[],
)
(options, args) = E.start(parser, argv=argv, add_output_options=True)
if not options.methods:
options.methods = ["summary"]
table = pandas.read_csv(options.stdin, options.delimiter)
options.stdout.write("metric\tcount\tpercent\tinfo\n")
for method in options.methods:
label = re.sub("-", "_", method)
if method == "summary":
for category, count, denominator, info in compute_table_summary(
table):
options.stdout.write("\t".join(
map(str, (category, count,
iotools.pretty_percent(count, denominator,
na=""), info))) + "\n")
elif method == "column-describe":
df = table.describe().T.stack()
with E.open_output_file(label) as outf:
outf.write("label\tcategory\tvalue\n")
df.to_csv(outf, sep="\t")
elif method == "row-describe":
df = table.T.describe().stack()
with E.open_output_file(label) as outf:
outf.write("label\tcategory\tvalue\n")
df.to_csv(outf, sep="\t")
E.stop()
def main(argv=None):
parser = E.OptionParser(
version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option(
"-s", "--species", dest="species", type="string",
help="species to use [default=%default].")
parser.add_option(
"-i", "--slims", dest="filename_slims", type="string",
help="filename with GO SLIM categories "
"[default=%default].")
parser.add_option(
"-g", "--genes-tsv-file", dest="filename_genes", type="string",
help="filename with genes to analyse "
"[default=%default].")
parser.add_option(
"-b", "--background-tsv-file", dest="filename_background",
type="string",
help="filename with background genes to analyse "
"[default=%default].")
parser.add_option(
"-m", "--min-counts", dest="minimum_counts",
type="int",
help="minimum count - ignore all categories that have "
"fewer than # number of genes"
" [default=%default].")
parser.add_option(
"-o", "--sort-order", dest="sort_order", type="choice",
choices=("fdr", "pvalue", "ratio"),
help="output sort order [default=%default].")
parser.add_option(
"--ontology", dest="ontology", type="string",
action="append",
help="go ontologies to analyze. Ontologies are tested "
"separately [default=%default].")
parser.add_option(
"-t", "--threshold", dest="threshold", type="float",
help="significance threshold [>1.0 = all ]. If --fdr is set, this "
"refers to the fdr, otherwise it is a cutoff for p-values.")
parser.add_option(
"--filename-dump", dest="filename_dump", type="string",
help="dump GO category assignments into a flatfile "
"[default=%default].")
parser.add_option(
"--gene2name-map-tsv-file", dest="filename_gene2name", type="string",
help="optional filename mapping gene identifiers to gene names "
"[default=%default].")
parser.add_option(
"--filename-ontology", dest="filename_ontology", type="string",
help="filename with ontology in OBO format [default=%default].")
parser.add_option(
"--filename-input", dest="filename_input", type="string",
help="read GO category assignments from a flatfile "
"[default=%default].")
parser.add_option(
"--sample-size", dest="sample", type="int",
help="do sampling (with # samples) [default=%default].")
parser.add_option(
"--filename-output-pattern", "--output-filename-pattern",
dest="output_filename_pattern", type="string",
help="pattern with output filename pattern "
"(should contain: %(go)s and %(section)s ) [default=%default]")
parser.add_option(
"--fdr", dest="fdr", action="store_true",
help="calculate and filter by FDR default=%default].")
parser.add_option(
"--go2goslim", dest="go2goslim", action="store_true",
help="convert go assignments in STDIN to goslim assignments and "
"write to STDOUT [default=%default].")
parser.add_option(
"--gene-pattern", dest="gene_pattern", type="string",
help="pattern to transform identifiers to GO gene names "
"[default=%default].")
parser.add_option(
"--filename-map-slims", dest="filename_map_slims", type="string",
help="write mapping between GO categories and GOSlims "
"[default=%default].")
parser.add_option(
"--get-genes", dest="get_genes", type="string",
help="list all genes in the with a certain GOID [default=%default].")
parser.add_option(
"--strict", dest="strict", action="store_true",
help="require all genes in foreground to be part of background. "
"If not set, genes in foreground will be added to the background "
"[default=%default].")
parser.add_option(
"-q", "--fdr-method", dest="qvalue_method", type="choice",
choices=("empirical", "storey", "BH"),
help="method to perform multiple testing correction by controlling "
"the fdr [default=%default].")
parser.add_option(
"--pairwise", dest="compute_pairwise", action="store_true",
help="compute pairwise enrichment for multiple gene lists. "
"[default=%default].")
# parser.add_option( "--fdr-lambda", dest="qvalue_lambda", type="float",
# help="fdr computation: lambda [default=%default]." )
# parser.add_option( "--qvalue-pi0-method", dest="qvalue_pi0_method", type="choice",
# choices = ("smoother", "bootstrap" ),
# help="fdr computation: method for estimating pi0 [default=%default]." )
parser.set_defaults(species=None,
filename_genes="-",
filename_background=None,
filename_slims=None,
minimum_counts=0,
ontology=[],
filename_dump=None,
sample=0,
fdr=False,
output_filename_pattern=None,
threshold=0.05,
filename_map_slims=None,
gene_pattern=None,
sort_order="ratio",
get_genes=None,
strict=False,
qvalue_method="empirical",
pairs_min_observed_counts=3,
compute_pairwise=False,
filename_gene2name=None
)
(options, args) = E.start(parser, add_database_options=True)
if options.go2goslim:
GO.convertGo2Goslim(options)
E.stop()
sys.exit(0)
if options.fdr and options.sample == 0:
E.warn("fdr will be computed without sampling")
#############################################################
# dump GO
if options.filename_dump:
# set default orthologies to GO
if not options.ontology:
options.ontology = [
"biol_process", "mol_function", "cell_location"]
E.info("dumping GO categories to %s" % (options.filename_dump))
dbhandle = database.connect(url=options.database_url)
outfile = iotools.open_file(options.filename_dump, "w", create_dir=True)
GO.DumpGOFromDatabase(outfile,
dbhandle,
options)
outfile.close()
E.stop()
sys.exit(0)
#############################################################
# read GO categories from file
if options.filename_input:
E.info("reading association of categories and genes from %s" %
(options.filename_input))
infile = iotools.open_file(options.filename_input)
gene2gos, go2infos = GO.ReadGene2GOFromFile(infile)
infile.close()
if options.filename_gene2name:
E.info("reading gene identifier to gene name mapping from %s" %
options.filename_gene2name)
infile = iotools.open_file(options.filename_gene2name)
gene2name = iotools.read_map(infile, has_header=True)
infile.close()
E.info("read %i gene names for %i gene identifiers" %
(len(set(gene2name.values())),
len(gene2name)))
else:
# use identity mapping
gene2name = dict([(x, x) for x in list(gene2gos.keys())])
#############################################################
# read GO ontology from file
if options.filename_ontology:
E.info("reading ontology from %s" % (options.filename_ontology))
infile = iotools.open_file(options.filename_ontology)
ontology = GO.readOntology(infile)
infile.close()
def _g():
return collections.defaultdict(GO.GOInfo)
go2infos = collections.defaultdict(_g)
# substitute go2infos
for go in list(ontology.values()):
go2infos[go.mNameSpace][go.mId] = GO.GOInfo(
go.mId,
go_type=go.mNameSpace,
description=go.mName)
#############################################################
# get foreground gene list
input_foreground, genelists = GO.ReadGeneLists(
options.filename_genes,
gene_pattern=options.gene_pattern)
E.info("read %i genes for forground in %i gene lists" %
(len(input_foreground), len(genelists)))
#############################################################
# get background
if options.filename_background:
# nick - bug fix: background is the first tuple element from
# ReadGeneLists
input_background = GO.ReadGeneLists(
options.filename_background,
gene_pattern=options.gene_pattern)[0]
E.info("read %i genes for background" % len(input_background))
else:
input_background = None
#############################################################
# sort out which ontologies to test
if not options.ontology:
if options.filename_input:
options.ontology = list(gene2gos.keys())
E.info("found %i ontologies: %s" %
(len(options.ontology), options.ontology))
summary = []
summary.append("\t".join((
"genelist",
"ontology",
"significant",
"threshold",
"ngenes",
"ncategories",
"nmaps",
"nforegound",
"nforeground_mapped",
"nbackground",
"nbackground_mapped",
"nsample_counts",
"nbackground_counts",
"psample_assignments",
"pbackground_assignments",
"messages")) + "\n")
#############################################################
# get go categories for genes
for test_ontology in sorted(options.ontology):
# store results for aggregate output of multiple gene lists
all_results = []
all_significant_results = []
all_genelists_with_results = []
E.info("working on ontology %s" % test_ontology)
#############################################################
# get/read association of GO categories to genes
if options.filename_input:
gene2go, go2info = gene2gos[test_ontology], go2infos[test_ontology]
else:
E.info("reading data from database ...")
dbhandle.Connect(options)
gene2go, go2info = GO.ReadGene2GOFromDatabase(
dbhandle,
test_ontology,
options.database, options.species)
E.info("finished")
if len(go2info) == 0:
E.warn(
"could not find information for terms - "
"could be mismatch between ontologies")
ngenes, ncategories, nmaps, counts_per_category = GO.CountGO(gene2go)
E.info("assignments found: %i genes mapped to %i categories "
"(%i maps)" %
(ngenes, ncategories, nmaps))
if options.minimum_counts > 0:
to_remove = set(
[x for x, y in counts_per_category.items()
if y < options.minimum_counts])
E.info("removing %i categories with less than %i genes" %
(len(to_remove), options.minimum_counts))
GO.removeCategories(gene2go, to_remove)
ngenes, ncategories, nmaps, counts_per_category = \
GO.CountGO(gene2go)
E.info("assignments after filtering: %i genes mapped "
"to %i categories (%i maps)" % (
ngenes, ncategories, nmaps))
for genelist_name, foreground in sorted(genelists.items()):
msgs = []
E.info("processing %s with %i genes" %
(genelist_name, len(foreground)))
##################################################################
##################################################################
##################################################################
# build background - reconcile with foreground
##################################################################
if input_background is None:
background = list(gene2go.keys())
else:
background = list(input_background)
# nick - bug-fix backgorund included the foreground in a tuple.
# background is the first tuple element
missing = foreground.difference(set(background))
if options.strict:
assert len(missing) == 0, \
"%i genes in foreground but not in background: %s" % (
len(missing), str(missing))
else:
if len(missing) != 0:
E.warn("%i genes in foreground that are not in "
"background - added to background of %i" %
(len(missing), len(background)))
background.extend(missing)
E.info("(unfiltered) foreground=%i, background=%i" %
(len(foreground), len(background)))
# sort foreground and background, important for reproducibility
# under random seed
foreground = sorted(foreground)
background = sorted(background)
#############################################################
# sanity checks:
# are all of the foreground genes in the dataset
# missing = set(genes).difference( set(gene2go.keys()) )
# assert len(missing) == 0, "%i genes in foreground set without GO annotation: %s" % (len(missing), str(missing))
#############################################################
# read GO slims and map GO categories to GO slim categories
if options.filename_slims:
go_slims = GO.GetGOSlims(
iotools.open_file(options.filename_slims, "r"))
if options.loglevel >= 1:
v = set()
for x in list(go_slims.values()):
for xx in x:
v.add(xx)
options.stdlog.write(
"# read go slims from %s: go=%i, slim=%i\n" %
(options.filename_slims,
len(go_slims),
len(v)))
if options.filename_map_slims:
if options.filename_map_slims == "-":
outfile = options.stdout
else:
outfile = iotools.open_file(
options.filename_map_slims, "w")
outfile.write("GO\tGOSlim\n")
for go, go_slim in sorted(list(go_slims.items())):
outfile.write("%s\t%s\n" % (go, go_slim))
if outfile != options.stdout:
outfile.close()
gene2go = GO.MapGO2Slims(gene2go, go_slims, ontology=ontology)
if options.loglevel >= 1:
ngenes, ncategories, nmaps, counts_per_category = \
GO.CountGO(gene2go)
options.stdlog.write(
"# after go slim filtering: %i genes mapped to "
"%i categories (%i maps)\n" % (
ngenes, ncategories, nmaps))
#############################################################
# Just dump out the gene list
if options.get_genes:
fg, bg, ng = [], [], []
for gene, vv in list(gene2go.items()):
for v in vv:
if v.mGOId == options.get_genes:
if gene in genes:
fg.append(gene)
elif gene in background:
bg.append(gene)
else:
ng.append(gene)
# skip to next GO class
if not (bg or ng):
continue
options.stdout.write(
"# genes in GO category %s\n" % options.get_genes)
options.stdout.write("gene\tset\n")
for x in sorted(fg):
options.stdout.write("%s\t%s\n" % ("fg", x))
for x in sorted(bg):
options.stdout.write("%s\t%s\n" % ("bg", x))
for x in sorted(ng):
options.stdout.write("%s\t%s\n" % ("ng", x))
E.info("nfg=%i, nbg=%i, nng=%i" % (len(fg), len(bg), len(ng)))
E.stop()
sys.exit(0)
#############################################################
outfile = GO.getFileName(options,
go=test_ontology,
section='foreground',
set=genelist_name)
outfile.write("gene_id\n%s\n" % ("\n".join(sorted(foreground))))
if options.output_filename_pattern:
outfile.close()
outfile = GO.getFileName(options,
go=test_ontology,
section='background',
set=genelist_name)
# Jethro bug fix - see section 'build background' for assignment
outfile.write("gene_id\n%s\n" % ("\n".join(sorted(background))))
if options.output_filename_pattern:
outfile.close()
#############################################################
# do the analysis
go_results = GO.AnalyseGO(gene2go, foreground, background)
if len(go_results.mSampleGenes) == 0:
E.warn("%s: no genes with GO categories - analysis aborted" %
genelist_name)
continue
pairs = list(go_results.mResults.items())
#############################################################
# calculate fdr for each hypothesis
if options.fdr:
fdrs, samples, method = GO.computeFDRs(go_results,
foreground,
background,
options,
test_ontology,
gene2go,
go2info)
for x, v in enumerate(pairs):
v[1].mQValue = fdrs[v[0]][0]
else:
fdrs, samples, method = {}, {}, None
msgs.append("fdr=%s" % method)
if options.sort_order == "fdr":
pairs.sort(key=lambda x: x[1].mQValue)
elif options.sort_order == "ratio":
pairs.sort(key=lambda x: x[1].mRatio)
elif options.sort_order == "pvalue":
pairs.sort(key=lambda x: x[1].mPValue)
#############################################################
#############################################################
#############################################################
# output the full result
outfile = GO.getFileName(options,
go=test_ontology,
section='overall',
set=genelist_name)
GO.outputResults(
outfile, pairs, go2info, options, fdrs=fdrs, samples=samples)
if options.output_filename_pattern:
outfile.close()
#############################################################
#############################################################
#############################################################
# filter significant results and output
filtered_pairs = GO.selectSignificantResults(pairs, fdrs, options)
nselected = len(filtered_pairs)
nselected_up = len([x for x in filtered_pairs if x[1].mRatio > 1])
nselected_down = len(
[x for x in filtered_pairs if x[1].mRatio < 1])
assert nselected_up + nselected_down == nselected
outfile = GO.getFileName(options,
go=test_ontology,
section='results',
set=genelist_name)
GO.outputResults(outfile,
filtered_pairs,
go2info,
options,
fdrs=fdrs,
samples=samples)
if options.output_filename_pattern:
outfile.close()
#############################################################
#############################################################
#############################################################
# save results for multi-gene-list analysis
all_results.append(pairs)
all_significant_results.append(filtered_pairs)
all_genelists_with_results.append(genelist_name)
#############################################################
#############################################################
#############################################################
# output parameters
ngenes, ncategories, nmaps, counts_per_category = \
GO.CountGO(gene2go)
outfile = GO.getFileName(options,
go=test_ontology,
section='parameters',
set=genelist_name)
nbackground = len(background)
if nbackground == 0:
nbackground = len(go_results.mBackgroundGenes)
outfile.write(
"# input go mappings for gene list '%s' and category '%s'\n" %
(genelist_name, test_ontology))
outfile.write("parameter\tvalue\tdescription\n")
outfile.write("mapped_genes\t%i\tmapped genes\n" % ngenes)
outfile.write(
"mapped_categories\t%i\tmapped categories\n" % ncategories)
outfile.write("mappings\t%i\tmappings\n" % nmaps)
outfile.write("genes_in_fg\t%i\tgenes in foreground\n" %
len(foreground))
outfile.write(
"genes_in_fg_with_assignment\t%i\tgenes in foreground with GO assignments\n" %
(len(go_results.mSampleGenes)))
outfile.write(
"genes_in_bg\t%i\tinput background\n" % nbackground)
outfile.write(
"genes_in_bg_with_assignment\t%i\tgenes in background with GO assignments\n" % (
len(go_results.mBackgroundGenes)))
outfile.write(
"associations_in_fg\t%i\tassociations in sample\n" %
go_results.mSampleCountsTotal)
outfile.write(
"associations_in_bg\t%i\tassociations in background\n" %
go_results.mBackgroundCountsTotal)
outfile.write(
"percent_genes_in_fg_with_association\t%s\tpercent genes in sample with GO assignments\n" % (
iotools.pretty_percent(len(go_results.mSampleGenes),
len(foreground), "%5.2f")))
outfile.write(
"percent_genes_in_bg_with_associations\t%s\tpercent genes background with GO assignments\n" % (
iotools.pretty_percent(len(go_results.mBackgroundGenes),
nbackground, "%5.2f")))
outfile.write(
"significant\t%i\tsignificant results reported\n" % nselected)
outfile.write(
"significant_up\t%i\tsignificant up-regulated results reported\n" % nselected_up)
outfile.write(
"significant_down\t%i\tsignificant up-regulated results reported\n" % nselected_down)
outfile.write(
"threshold\t%6.4f\tsignificance threshold\n" % options.threshold)
if options.output_filename_pattern:
outfile.close()
summary.append("\t".join(map(str, (
genelist_name,
test_ontology,
nselected,
options.threshold,
ngenes,
ncategories,
nmaps,
len(foreground),
len(go_results.mSampleGenes),
nbackground,
len(go_results.mBackgroundGenes),
go_results.mSampleCountsTotal,
go_results.mBackgroundCountsTotal,
iotools.pretty_percent(
len(go_results.mSampleGenes), len(foreground), "%5.2f"),
iotools.pretty_percent(
len(go_results.mBackgroundGenes), nbackground, "%5.2f"),
",".join(msgs)))) + "\n")
#############################################################
#############################################################
#############################################################
# output the fg patterns
outfile = GO.getFileName(options,
go=test_ontology,
section='withgenes',
set=genelist_name)
GO.outputResults(outfile, pairs, go2info, options,
fdrs=fdrs,
samples=samples,
gene2go=gene2go,
foreground=foreground,
gene2name=gene2name)
if options.output_filename_pattern:
outfile.close()
if len(genelists) > 1:
###################################################################
# output various summary files
# significant results
GO.outputMultipleGeneListResults(all_significant_results,
all_genelists_with_results,
test_ontology,
go2info,
options,
section='significant')
# all results
GO.outputMultipleGeneListResults(all_results,
all_genelists_with_results,
test_ontology,
go2info,
options,
section='all')
if options.compute_pairwise:
GO.pairwiseGOEnrichment(all_results,
all_genelists_with_results,
test_ontology,
go2info,
options)
outfile_summary = options.stdout
outfile_summary.write("".join(summary))
E.stop()
def _write(outs, text, numerator, denominator, base):
percent = iotools.pretty_percent(numerator, denominator)
outs.write('%s\t%i\t%s\t%s\n' % (text, numerator, percent, base))
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: chain2psl.py 2899 2010-04-13 14:37:37Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-m", "--output-mismatches", dest="output_mismatches", action="store_true",
help="output mismatches [%default]")
parser.add_option("-a", "--output-matches", dest="output_matches", action="store_true",
help="output matches [%default]")
parser.add_option("-u", "--output-unique", dest="output_unique", action="store_true",
help="output unique positions [%default]")
parser.add_option("-r", "--restrict", dest="restrict", type="string",
help="restrict analysis to a chromosome pair (chr1:chr1:+) [%default]")
parser.set_defaults(
output_mismatches=False,
output_unique=False,
restrict=None
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.start(parser, argv=argv)
if len(args) != 2:
raise ValueError("expected two chain files")
filename_chain1, filename_chain2 = args
E.info("validating chain 1")
if not validateChain(iotools.open_file(filename_chain1)):
E.warn("validation failed - exiting")
return 1
E.info("validating chain 2")
if not validateChain(iotools.open_file(filename_chain2)):
E.warn("validation failed - exiting")
return 1
E.info("building pairs for %s" % filename_chain1)
pairs1 = buildPairs(iotools.open_file(filename_chain1))
E.info("read %i pairs" % len(pairs1))
E.info("building pairs for %s" % filename_chain2)
pairs2 = buildPairs(iotools.open_file(filename_chain2))
E.info("read %i pairs" % len(pairs2))
if options.restrict:
restrict = tuple(options.restrict.split(":"))
pairs1 = {restrict: pairs1[restrict]}
pairs2 = {restrict: pairs2[restrict]}
E.info("comparing 1 -> 2")
comparison1 = compareChains(pairs1, pairs2)
E.info("comparing 2 -> 1")
comparison2 = compareChains(pairs2, pairs1)
all_keys = sorted(list(set(list(comparison1.keys()) + list(comparison2.keys()))))
outfile = options.stdout
headers = ("mapped", "identical", "different", "unique")
outfile.write("contig1\tcontig2\tstrand\t%s\t%s\t%s\t%s\n" %
(
"\t".join(["%s1" % x for x in headers]),
"\t".join(["p%s1" % x for x in headers]),
"\t".join(["%s2" % x for x in headers]),
"\t".join(["p%s2" % x for x in headers])))
totals = E.Counter()
for key in all_keys:
outfile.write("%s\t%s\t%s" % key)
if key in comparison1:
c = comparison1[key]
outfile.write("\t%i\t%i\t%i\t%i\t" %
(c.total, c.same, c.different, c.unique))
outfile.write(
"\t".join([iotools.pretty_percent(x, c.total) for x in c]))
totals.total1 += c.total
totals.same1 += c.same
totals.different1 += c.different
totals.unique1 += c.unique
else:
outfile.write("\t%i\t%i\t%i\t%i\t" % (0, 0, 0, 0))
outfile.write("\t%i\t%i\t%i\t%i" % (0, 0, 0, 0))
if key in comparison2:
c = comparison2[key]
outfile.write("\t%i\t%i\t%i\t%i\t" %
(c.total, c.same, c.different, c.unique))
outfile.write(
"\t".join([iotools.pretty_percent(x, c.total) for x in c]))
totals.same2 += c.same
totals.total2 += c.total
totals.different2 += c.different
totals.unique2 += c.unique
else:
outfile.write("\t%i\t%i\t%i\t%i\t" % (0, 0, 0, 0))
outfile.write("\t%i\t%i\t%i\t%i" % (0, 0, 0, 0))
outfile.write("\n")
outfile.write("total\ttotal\t.\t")
outfile.write("\t".join(map(str, (totals.total1,
totals.same1,
totals.different1,
totals.unique1,
iotools.pretty_percent(
totals.total1, totals.total1),
iotools.pretty_percent(
totals.same1, totals.total1),
iotools.pretty_percent(
totals.different1, totals.total1),
iotools.pretty_percent(
totals.unique1, totals.total1),
totals.total2,
totals.same2,
totals.different2,
totals.unique2,
iotools.pretty_percent(
totals.total2, totals.total2),
iotools.pretty_percent(
totals.same2, totals.total2),
iotools.pretty_percent(
totals.different2, totals.total2),
iotools.pretty_percent(
totals.unique2, totals.total2),
))) + "\n")
# output mismapped residues
if options.output_mismatches or options.output_unique:
outputMismatches(pairs1, pairs2,
output_mismatches=options.output_mismatches,
output_unique=options.output_unique,
output_matches=options.output_matches,
)
# write footer and output benchmark information.
E.stop()