def _calculate_totals(table):
for (name, samples) in sorted(table.items()):
for (sample, libraries) in sorted(samples.items()):
for (library, contigs) in sorted(libraries.items()):
set_in(table, (name, sample, library),
_calculate_totals_in(contigs))
set_in(table, (name, sample, "*"), _calculate_totals_in(libraries))
set_in(table, (name, sample, "*", "*", "Size"),
get_in(table, (name, sample, library, "*", "Size")))
set_in(table, (name, "*", "*"), _calculate_totals_in(table))
set_in(table, (name, "*", "*", "*", "Size"),
get_in(table, (name, sample, "*", "*", "Size")))
def _open_se_sink(reads_type):
key = (name, reads_type)
if not get_in(sink_cache, key):
filename = ReadSink.get_filename(destination, reads_type.lower())
set_in(sink_cache, key, ReadSink.open(config.destination,
filename))
return key
def _initialize_tables(cls, target_name, intervals, readgroups):
subtables = {}
for (name, intervals) in intervals.iteritems():
size = sum((end - start) for (_, start, end) in intervals)
subtables[name] = {
"SE": 0,
"PE_1": 0,
"PE_2": 0,
"Collapsed": 0,
"Hits": 0,
"M": 0,
"I": 0,
"D": 0,
"Size": size
}
tables, mapping = {}, {}
for rg in readgroups.itervalues():
subtbl_copy = get_in(tables, (target_name, rg["SM"], rg["LB"]),
None)
if not subtbl_copy:
subtbl_copy = copy.deepcopy(subtables)
set_in(tables, (target_name, rg["SM"], rg["LB"]), subtbl_copy)
mapping[rg["ID"]] = subtbl_copy
return tables, mapping
def create_or_get_subtable(table, subtable_key, size):
subtable = get_in(table, subtable_key)
if subtable is None:
subtable = dict(READGROUP_TEMPLATE)
subtable["Size"] = size
set_in(table, subtable_key, subtable)
return subtable
def create_or_get_subtable(table, subtable_key, size):
subtable = get_in(table, subtable_key)
if subtable is None:
subtable = dict(READGROUP_TEMPLATE)
subtable["Size"] = size
set_in(table, subtable_key, subtable)
return subtable
def update_gtf_table(table, gtf, scaffolds, contig_prefix):
# Workaround for bug in Pysam, which mis-parses individual properties
# (e.g. exon_number) if these are not quoted. This does not apply to
# asDict, which uses a different parsing implementation (v0.7.8).
properties = gtf.asDict()
keys = (properties["gene_biotype"],
properties["gene_id"],
properties["transcript_id"],
int(properties["exon_number"]),
gtf.feature)
record = {"contig": contig_prefix + gtf.contig,
"start": gtf.start,
# In pysam, 'end' equals the past-the-end position
"end": gtf.end - 1,
"strand": gtf.strand,
"feature": gtf.feature,
"transcript": properties["transcript_id"]}
if record["contig"] in scaffolds:
contig = scaffolds[record["contig"]]
record["contig"] = contig["chrom"]
record["start"] += int(contig["chromStart"])
record["end"] += int(contig["chromStart"])
assert not get_in(table, keys), keys
set_in(table, keys, record)
def _read_coverage_tables(cls, key, filenames):
hits = nts = 0
for filename in filenames:
subtable = {}
read_coverage_table(subtable, filename)
for contigtable in get_in(subtable, key).itervalues():
hits += contigtable["Hits"]
nts += contigtable["M"]
return hits, nts
def _collect_clade_from(self, cache, p_node, c_node):
c_clade = get_in(cache, (p_node, c_node), set())
if not c_clade:
if self.is_leaf(c_node):
c_clade.add(c_node)
for n_node in self.connections[c_node]:
if n_node != p_node:
c_clade.update(self._collect_clade_from(cache, c_node, n_node))
set_in(cache, (p_node, c_node), frozenset(c_clade))
return c_clade
def _collect_clade_from(self, cache, p_node, c_node):
c_clade = get_in(cache, (p_node, c_node), set())
if not c_clade:
if self.is_leaf(c_node):
c_clade.add(c_node)
for n_node in self.connections[c_node]:
if n_node != p_node:
c_clade.update(
self._collect_clade_from(cache, c_node, n_node))
set_in(cache, (p_node, c_node), frozenset(c_clade))
return c_clade
def _read_raw_bam_stats(self, table):
for ((genome, target, sample, library), filenames) in self._in_raw_bams.iteritems():
subtable = {}
for filename in filenames:
read_coverage_table(subtable, filename)
key = (target, sample, library)
hits = 0
for contigtable in get_in(subtable, key).itervalues():
hits += contigtable["Hits"]
value = (hits, "# Total number of hits (prior to PCR duplicate filtering)")
set_in(table, (target, sample, library, genome, "hits_raw(%s)" % genome), value)
def _read_table(self, key, table, filename):
all_key = "all" if self._intervals else "genome"
with open(filename) as handle:
for line in handle:
fields = line.split("\t")
# 'all' is generated by coverageBed, as a catchall group
if (fields[0] == all_key) and (len(fields) == 5):
name = None
elif self._max_contigs_reached:
continue
elif (len(fields) > (3 + 4)):
# Probably a BED6 file, 4 columns are from bedTools
name = fields[3]
else:
name = fields[0]
ckey = key + (name, )
if not get_in(table, ckey, None):
set_in(table, ckey, [0] * (_MAX_DEPTH + 1))
depth = min(_MAX_DEPTH, int(fields[-4]))
get_in(table, ckey)[depth] += int(fields[-3])
def _read_table(self, key, table, filename):
all_key = "all" if self._intervals else "genome"
with open(filename) as handle:
for line in handle:
fields = line.split("\t")
# 'all' is generated by coverageBed, as a catchall group
if (fields[0] == all_key) and (len(fields) == 5):
name = None
elif self._max_contigs_reached:
continue
elif (len(fields) > (3 + 4)):
# Probably a BED6 file, 4 columns are from bedTools
name = fields[3]
else:
name = fields[0]
ckey = key + (name,)
if not get_in(table, ckey, None):
set_in(table, ckey, [0] * (_MAX_DEPTH + 1))
depth = min(_MAX_DEPTH, int(fields[-4]))
get_in(table, ckey)[depth] += int(fields[-3])
def convert_reads(config, destination, record, sink_cache):
# Source name is used, to re-merge split lanes
name = record.tags.get("PU_src")
destination = os.path.join(destination, name)
make_dirs(os.path.join(config.destination, destination))
def _open_se_sink(reads_type):
key = (name, reads_type)
if not get_in(sink_cache, key):
filename = ReadSink.get_filename(destination, reads_type.lower())
set_in(sink_cache, key, ReadSink.open(config.destination,
filename))
return key
for (reads_type, bam_files) in record.bams.iteritems():
# Processed reads are pre-aligned BAMs which have been cleaned up
if reads_type in ("Paired", "Processed"):
# Record "Single" reads; these may result from orphan SE reads
_open_se_sink("Single")
key = (name, "Paired")
if not get_in(sink_cache, key):
set_in(sink_cache, key,
PEReadSink.open(config.destination, destination))
else:
key = _open_se_sink(reads_type)
sink = get_in(sink_cache, key)
for filename in bam_files:
print("%sProcessing file %r" % (_INDENTATION * 4, filename))
with pysam.Samfile(filename) as handle:
def _keep_record(record):
return (record.qual >= config.min_quality) and \
(len(record.seq) >= config.min_length)
sink.write_records(record for record in handle
if _keep_record(record))
def convert_reads(config, destination, record, sink_cache):
# Source name is used, to re-merge split lanes
name = record.tags.get("PU_src")
destination = os.path.join(destination, name)
make_dirs(os.path.join(config.destination, destination))
def _open_se_sink(reads_type):
key = (name, reads_type)
if not get_in(sink_cache, key):
filename = ReadSink.get_filename(destination, reads_type.lower())
set_in(sink_cache, key, ReadSink.open(config.destination, filename))
return key
for (reads_type, bam_files) in record.bams.iteritems():
# Processed reads are pre-aligned BAMs which have been cleaned up
if reads_type in ("Paired", "Processed"):
# Record "Single" reads; these may result from orphan SE reads
_open_se_sink("Single")
key = (name, "Paired")
if not get_in(sink_cache, key):
set_in(sink_cache, key, PEReadSink.open(config.destination,
destination))
else:
key = _open_se_sink(reads_type)
sink = get_in(sink_cache, key)
for filename in bam_files:
print("%sProcessing file %r" % (_INDENTATION * 4, filename))
with pysam.Samfile(filename) as handle:
def _keep_record(record):
return (record.qual >= config.min_quality) and \
(len(record.seq) >= config.min_length)
sink.write_records(record for record in handle
if _keep_record(record))
def _read_lib_bam_stats(self, table):
for ((genome, target, sample, library), filenames) in self._in_lib_bams.iteritems():
subtable = {}
for filename in filenames:
read_coverage_table(subtable, filename)
key = (target, sample, library)
hits = nts = 0
for contigtable in get_in(subtable, key).itervalues():
hits += contigtable["Hits"]
nts += contigtable["M"]
value = (hits, "# Total number of hits (excluding any PCR duplicates)")
set_in(table, (target, sample, library, genome, "hits_unique(%s)" % genome), value)
set_in(table, (target, sample, library, genome, "hits_unique_nts(%s)" % genome), (nts, None))
def read_table(table, filename):
with open(filename) as table_file:
for record in parse_padded_table(table_file):
key = (record["Name"], record["Sample"], record["Library"],
record["Contig"])
if "*" in key:
continue
subtable = get_in(table, key, {"Size": int(record["Size"])})
assert int(subtable["Size"]) == int(record["Size"])
for field in ("Hits", "SE", "PE_1", "PE_2", "Collapsed", "M", "I",
"D"):
subtable[field] = subtable.get(field, 0) + int(
record.get(field, 0))
set_in(table, key, subtable)
def read_table(table, filename):
with open(filename) as table_file:
for record in parse_padded_table(table_file):
key = (record["Name"], record["Sample"], record["Library"], record["Contig"])
if "*" in key:
continue
subtable = get_in(table, key)
if subtable is None:
subtable = dict(READGROUP_TEMPLATE)
subtable["Size"] = int(record["Size"])
set_in(table, key, subtable)
assert int(subtable["Size"]) == int(record["Size"])
for key in READGROUP_TEMPLATE:
if key != "Size":
subtable[key] += int(record.get(key, 0))
def read_table(table, filename):
with open(filename) as table_file:
for record in parse_padded_table(table_file):
key = (record["Name"], record["Sample"], record["Library"],
record["Contig"])
if "*" in key:
continue
subtable = get_in(table, key)
if subtable is None:
subtable = dict(READGROUP_TEMPLATE)
subtable["Size"] = int(record["Size"])
set_in(table, key, subtable)
assert int(subtable["Size"]) == int(record["Size"])
for key in READGROUP_TEMPLATE:
if key != "Size":
subtable[key] += int(record.get(key, 0))
def _read_raw_bam_stats(self, table):
for ((genome, target, sample, library),
filenames) in self._in_raw_bams.iteritems():
subtable = {}
for filename in filenames:
read_coverage_table(subtable, filename)
key = (target, sample, library)
hits = 0
for contigtable in get_in(subtable, key).itervalues():
hits += contigtable["Hits"]
value = (
hits,
"# Total number of hits (prior to PCR duplicate filtering)")
set_in(table,
(target, sample, library, genome, "hits_raw(%s)" % genome),
value)
def _read_coverage_tables(cls, key, filenames):
hits = nts = 0
for filename in filenames:
subtable = {}
read_coverage_table(subtable, filename)
contigtables = get_in(subtable, key)
if contigtables is None:
raise NodeError("Error reading table %r; row not found:"
"\n %s ...\n\nIf files have been renamed "
"during the run, then please remove this file "
"in that it may be re-generated.\nHowever, "
"note that read-group tags in the BAM files "
"may not be correct!"
% (filename, " ".join(key)))
for contigtable in contigtables.itervalues():
hits += contigtable["Hits"]
nts += contigtable["M"]
return hits, nts
def _read_lib_bam_stats(self, table):
for ((genome, target, sample, library),
filenames) in self._in_lib_bams.iteritems():
subtable = {}
for filename in filenames:
read_coverage_table(subtable, filename)
key = (target, sample, library)
hits = nts = 0
for contigtable in get_in(subtable, key).itervalues():
hits += contigtable["Hits"]
nts += contigtable["M"]
value = (hits,
"# Total number of hits (excluding any PCR duplicates)")
set_in(
table,
(target, sample, library, genome, "hits_unique(%s)" % genome),
value)
set_in(table, (target, sample, library, genome,
"hits_unique_nts(%s)" % genome), (nts, None))
def _read_coverage_tables(cls, key, filenames):
hits = nts = 0
for filename in filenames:
subtable = {}
read_coverage_table(subtable, filename)
contigtables = get_in(subtable, key)
if contigtables is None:
raise NodeError(
"Error reading table %r; row not found:"
"\n %s ...\n\nIf files have been renamed "
"during the run, then please remove this file "
"in that it may be re-generated.\nHowever, "
"note that read-group tags in the BAM files "
"may not be correct!" % (filename, " ".join(key))
)
for contigtable in contigtables.itervalues():
hits += contigtable["Hits"]
nts += contigtable["M"]
return hits, nts
def test_get_in__get_default_one_keyword():
assert_equal(utils.get_in({1: 2}, [2]), None)
def test_get_in__get_value_three_keywords():
assert_equal(utils.get_in({1: {2: {3: 4}}}, [1, 2, 3]), 4)
def test_get_in__get_value_two_keywords():
assert_equal(utils.get_in({1: {2: 3}}, [1, 2]), 3)
def test_get_in__get_value_one_keyword():
assert_equal(utils.get_in({1: 2}, [1]), 2)
def test_get_in__get_default_three_keywords_fail_at_third_with_default():
assert_equal(utils.get_in({1: {2: {3: 4}}}, [1, 2, 4], "other"), "other")
def test_get_in__get_default_one_keyword():
assert_equal(utils.get_in({1 : 2}, [2]), None)
def test_get_in__get_default_one_keyword_with_default():
assert_equal(utils.get_in({1 : 2}, [2], "other"), "other")
def test_get_in__get_default_three_keywords_fail_at_third():
assert_equal(utils.get_in({1 : {2 : {3 : 4}}}, [1, 2, 4]), None)
def test_get_in__get_default_three_keywords_fail_at_third_with_default():
assert_equal(utils.get_in({1 : {2 : {3 : 4}}}, [1, 2, 4], "other"), "other")
def test_get_in__iterator_keywords():
assert_equal(utils.get_in({1 : {2 : {3 : 4}}}, iter([1, 2, 3])), 4)
def test_get_in__get_default_one_keyword_with_default():
assert_equal(utils.get_in({1: 2}, [2], "other"), "other")
def test_get_in__get_default_three_keywords_fail_at_third():
assert_equal(utils.get_in({1: {2: {3: 4}}}, [1, 2, 4]), None)
def test_get_in__get_value_three_keywords():
assert_equal(utils.get_in({1 : {2 : {3 : 4}}}, [1, 2, 3]), 4)
def test_get_in__iterator_keywords():
assert_equal(utils.get_in({1: {2: {3: 4}}}, iter([1, 2, 3])), 4)
def test_get_in__get_value_two_keywords():
assert_equal(utils.get_in({1 : {2 : 3}}, [1, 2]), 3)
def test_get_in__get_value_one_keyword():
assert_equal(utils.get_in({1 : 2}, [1]), 2)
def _open_se_sink(reads_type):
key = (name, reads_type)
if not get_in(sink_cache, key):
filename = ReadSink.get_filename(destination, reads_type.lower())
set_in(sink_cache, key, ReadSink.open(config.destination, filename))
return key
