def get_untrimmed_coverage_from_output(log, sample, assembly_pth, coverage,
velvet):
log.info("Screening contigs for coverage")
if not velvet:
regex = re.compile("({}).*:(\d+)".format(
get_user_param("headers", "trinity")))
else:
regex = re.compile("({}.*):(\d+)".format(
get_user_param("headers", "velvet")))
# setup starting values
previous_match = None
contig_depth = []
contig_data = OrderedDict()
overall_coverage = []
overall_length = []
overall_count = 0
overall_contigs = {}
upcc = os.path.join(assembly_pth,
'{}-UNTRIMMED-per-contig-coverage.txt'.format(sample))
with open(coverage, 'rU') as infile:
with open(upcc, 'w') as unt_per_contig_cov:
# read header line
gatk_header = infile.readline()
# write headers to outfiles
unt_per_contig_cov.write(
"name\tbeginning-length\tbeginning-mean-cov\n")
for line in infile:
ls = line.split()
search = regex.search(ls[0])
match_name, pos = search.groups()
if previous_match is None or match_name == previous_match:
# hold onto current match_name
previous_match = match_name
# compute metrics on current position
#contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
elif match_name != previous_match:
metadata = compute_coverage_metrics(contig_depth,
trim=False)
unt_per_contig_cov.write("{}\t{}\t{}\n".format(
previous_match, metadata["beginning-length"],
metadata["beginning-mean-cov"]))
overall_contigs[previous_match] = metadata
overall_count += 1
overall_coverage.append(metadata["beginning-mean-cov"])
overall_length.append(metadata["beginning-length"])
# reset previous match to current
previous_match = match_name
# reset containers
contig_depth = []
contig_data = OrderedDict()
# compute metrics on current first position
contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
log.info(
"\t{} contigs, mean coverage = {:.1f}, mean length = {:.1f}".format(
overall_count, numpy.mean(overall_coverage),
numpy.mean(overall_length)))
return overall_contigs
def get_untrimmed_coverage_from_output(log, sample, assembly_pth, coverage, velvet):
log.info("Screening contigs for coverage")
if not velvet:
regex = re.compile("({}).*:(\d+)".format(get_user_param("headers", "trinity")))
else:
regex = re.compile("({}.*):(\d+)".format(get_user_param("headers", "velvet")))
# setup starting values
previous_match = None
contig_depth = []
contig_data = OrderedDict()
overall_coverage = []
overall_length = []
overall_count = 0
overall_contigs = {}
upcc = os.path.join(
assembly_pth,
'{}-UNTRIMMED-per-contig-coverage.txt'.format(sample)
)
with open(coverage, 'rU') as infile:
with open(upcc, 'w') as unt_per_contig_cov:
# read header line
gatk_header = infile.readline()
# write headers to outfiles
unt_per_contig_cov.write("name\tbeginning-length\tbeginning-mean-cov\n")
for line in infile:
ls = line.split()
search = regex.search(ls[0])
match_name, pos = search.groups()
if previous_match is None or match_name == previous_match:
# hold onto current match_name
previous_match = match_name
# compute metrics on current position
#contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
elif match_name != previous_match:
metadata = compute_coverage_metrics(contig_depth, trim=False)
unt_per_contig_cov.write("{}\t{}\t{}\n".format(
previous_match,
metadata["beginning-length"],
metadata["beginning-mean-cov"]
))
overall_contigs[previous_match] = metadata
overall_count += 1
overall_coverage.append(metadata["beginning-mean-cov"])
overall_length.append(metadata["beginning-length"])
# reset previous match to current
previous_match = match_name
# reset containers
contig_depth = []
contig_data = OrderedDict()
# compute metrics on current first position
contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
log.info("\t{} contigs, mean coverage = {:.1f}, mean length = {:.1f}".format(
overall_count,
numpy.mean(overall_coverage),
numpy.mean(overall_length)
))
return overall_contigs
def test_config_parameters(self):
"""Test that config parameters exist"""
for parameter in self.parameters:
param = get_user_param(parameter[0], parameter[1])
expected = parameter[2]
self.assertEqual(
param, expected,
"Config entry {} != {} (expected)".format(param, expected))
def test_config_parameters(self):
"""Test that config parameters exist"""
for parameter in self.parameters:
param = get_user_param(parameter[0], parameter[1])
expected = parameter[2]
self.assertEqual(
param,
expected,
"Config entry {} != {} (expected)".format(param, expected)
)
(c) 2014 Brant Faircloth || http://faircloth-lab.org/
All rights reserved.
This code is distributed under a 3-clause BSD license. Please see
LICENSE.txt for more information.
Created on 26 June 2014 17:13 PDT (-0700)
"""
import os
import subprocess
from phyluce.pth import get_user_path, get_user_param
JAVA = get_user_param("java", "executable")
JAVA_PARAMS = get_user_param("java", "mem")
JAR_PATH = get_user_path("java", "jar")
def new_bam_name(bam, append):
pth, bamfname = os.path.split(bam)
bamfname = os.path.splitext(bamfname)[0]
new_bamfname = "{}-{}.bam".format(bamfname, append)
new_bam = os.path.join(pth, new_bamfname)
return new_bam
def create_reference_dict(log, sample, sample_dir, reference):
log.info("Creating FASTA dict for {}".format(sample))
outf = os.path.splitext(reference)[0] + ".dict"
def get_trimmed_coverage_from_output(log, sample, assembly_pth, coverage,
assembler):
log.info("Screening and filtering contigs for coverage (3x ends, 5x avg.)")
if assembler == "trinity":
regex = re.compile("({}).*:(\d+)".format(
get_user_param("headers", "trinity")))
elif assembler == "velvet":
regex = re.compile("({}.*):(\d+)".format(
get_user_param("headers", "velvet")))
elif assembler == "abyss":
regex = re.compile("({}.*):(\d+)".format(
get_user_param("headers", "abyss")))
elif assembler == "idba":
regex = re.compile("({}.*):(\d+)".format(
get_user_param("headers", "idba")))
# setup starting values
previous_match = None
contig_depth = []
contig_data = OrderedDict()
overall_coverage = []
overall_length = []
overall_count = 1
overall_contigs = {}
pbc = os.path.join(assembly_pth,
'{}-TRIMMED-per-base-coverage.txt.gz'.format(sample))
pcc = os.path.join(assembly_pth,
'{}-TRIMMED-per-contig-coverage.txt'.format(sample))
upcc = os.path.join(assembly_pth,
'{}-UNTRIMMED-per-contig-coverage.txt'.format(sample))
with open(coverage, 'rU') as infile:
with gzip.open(pbc, 'w') as per_base_cov:
with open(pcc, 'w') as per_contig_cov:
with open(upcc, 'w') as unt_per_contig_cov:
# read header line
gatk_header = infile.readline()
# write headers to outfiles
per_contig_cov.write(
"name\tbeginning-length\tbeginning-mean-cov\ttrim-start\ttrim-end\tend-length\tend-mean-cov\n"
)
unt_per_contig_cov.write(
"name\tbeginning-length\tbeginning-mean-cov\n")
per_base_cov.write(gatk_header)
for line in infile:
ls = line.split()
search = regex.search(ls[0])
match_name, pos = search.groups()
if previous_match is None or match_name == previous_match:
# hold onto current match_name
previous_match = match_name
# compute metrics on current position
contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
elif match_name != previous_match:
metadata = compute_coverage_metrics(contig_depth,
trim=True)
unt_per_contig_cov.write("{}\t{}\t{}\n".format(
previous_match, metadata["beginning-length"],
metadata["beginning-mean-cov"]))
if metadata["ending-mean-cov"] >= 5.0:
per_contig_cov.write(
"{}\t{}\t{}\t{}\t{}\t{}\t{}\n".format(
previous_match,
metadata["beginning-length"],
metadata["beginning-mean-cov"],
metadata["trim-start"],
metadata["trim-end"],
metadata["ending-length"],
metadata["ending-mean-cov"]))
for pos, line in contig_data.iteritems():
if pos - 1 >= metadata[
"trim-start"] and pos - 1 < metadata[
"trim-end"]:
per_base_cov.write(line)
overall_contigs[previous_match] = metadata
overall_count += 1
overall_coverage.append(
metadata["ending-mean-cov"])
overall_length.append(
metadata["ending-length"])
# reset previous match to current
previous_match = match_name
# reset containers
contig_depth = []
contig_data = OrderedDict()
# compute metrics on current first position
contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
log.info(
"\t{} contigs, mean coverage = {:.1f}, mean length = {:.1f}".format(
overall_count, numpy.mean(overall_coverage),
numpy.mean(overall_length)))
return overall_contigs
Created on 26 June 2014 17:17 PDT (-0700)
"""
import os
import re
import gzip
import glob
import numpy
import subprocess
from collections import OrderedDict
from phyluce.pth import get_user_param, get_user_path
from Bio import SeqIO
JAVA = get_user_param("java", "executable")
JAVA_PARAMS = get_user_param("java", "mem")
JAR_PATH = get_user_path("java", "jar")
GATK = get_user_param("java", "gatk")
def coverage(log, sample, assembly_pth, assembly, cores, bam):
log.info("Computing coverage with GATK for {}".format(sample))
cwd = os.getcwd()
# move into reference directory
os.chdir(assembly_pth)
cmd = [
JAVA, JAVA_PARAMS, "-jar",
os.path.join(JAR_PATH, GATK), "-T", "DepthOfCoverage", "-R", assembly,
"-I", bam, "-o", "{}-coverage".format(sample), "-nt",
str(cores), "--omitIntervalStatistics", "--omitLocusTable"
def get_trimmed_coverage_from_output(log, sample, assembly_pth, coverage, assembler):
log.info("Screening and filtering contigs for coverage (3x ends, 5x avg.)")
if assembler == "trinity":
regex = re.compile("({}).*:(\d+)".format(get_user_param("headers", "trinity")))
elif assembler == "velvet":
regex = re.compile("({}.*):(\d+)".format(get_user_param("headers", "velvet")))
elif assembler == "abyss":
regex = re.compile("({}.*):(\d+)".format(get_user_param("headers", "abyss")))
elif assembler == "idba":
regex = re.compile("({}.*):(\d+)".format(get_user_param("headers", "idba")))
# setup starting values
previous_match = None
contig_depth = []
contig_data = OrderedDict()
overall_coverage = []
overall_length = []
overall_count = 1
overall_contigs = {}
pbc = os.path.join(
assembly_pth,
'{}-TRIMMED-per-base-coverage.txt.gz'.format(sample)
)
pcc = os.path.join(
assembly_pth,
'{}-TRIMMED-per-contig-coverage.txt'.format(sample)
)
upcc = os.path.join(
assembly_pth,
'{}-UNTRIMMED-per-contig-coverage.txt'.format(sample)
)
with open(coverage, 'rU') as infile:
with gzip.open(pbc, 'w') as per_base_cov:
with open(pcc, 'w') as per_contig_cov:
with open(upcc, 'w') as unt_per_contig_cov:
# read header line
gatk_header = infile.readline()
# write headers to outfiles
per_contig_cov.write("name\tbeginning-length\tbeginning-mean-cov\ttrim-start\ttrim-end\tend-length\tend-mean-cov\n")
unt_per_contig_cov.write("name\tbeginning-length\tbeginning-mean-cov\n")
per_base_cov.write(gatk_header)
for line in infile:
ls = line.split()
search = regex.search(ls[0])
match_name, pos = search.groups()
if previous_match is None or match_name == previous_match:
# hold onto current match_name
previous_match = match_name
# compute metrics on current position
contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
elif match_name != previous_match:
metadata = compute_coverage_metrics(contig_depth, trim=True)
unt_per_contig_cov.write("{}\t{}\t{}\n".format(
previous_match,
metadata["beginning-length"],
metadata["beginning-mean-cov"]
))
if metadata["ending-mean-cov"] >= 5.0:
per_contig_cov.write("{}\t{}\t{}\t{}\t{}\t{}\t{}\n".format(
previous_match,
metadata["beginning-length"],
metadata["beginning-mean-cov"],
metadata["trim-start"],
metadata["trim-end"],
metadata["ending-length"],
metadata["ending-mean-cov"]
))
for pos, line in contig_data.iteritems():
if pos-1 >= metadata["trim-start"] and pos-1 < metadata["trim-end"]:
per_base_cov.write(line)
overall_contigs[previous_match] = metadata
overall_count += 1
overall_coverage.append(metadata["ending-mean-cov"])
overall_length.append(metadata["ending-length"])
# reset previous match to current
previous_match = match_name
# reset containers
contig_depth = []
contig_data = OrderedDict()
# compute metrics on current first position
contig_data[int(pos)] = line
contig_depth.append(int(ls[1]))
log.info("\t{} contigs, mean coverage = {:.1f}, mean length = {:.1f}".format(
overall_count,
numpy.mean(overall_coverage),
numpy.mean(overall_length)
))
return overall_contigs
