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AmpliconSuite-pipeline.py
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#!/usr/bin/env python
# author: Jens Luebeck (jluebeck [at] ucsd.edu)
import argparse
from datetime import datetime
import json
import logging
import os
import socket
from subprocess import *
import sys
import tarfile
import time
import urllib.request
from paalib import check_reference, cnv_prefilter
__version__ = "1.2.1"
PY3_PATH = "python3" # updated by command-line arg if specified
metadata_dict = {} # stores the run metadata (bioinformatic metadata)
sample_info_dict = {} # stores the sample metadata
def run_bwa(ref_fasta, fastqs, outdir, sname, nthreads, samtools, usingDeprecatedSamtools=False):
outname = outdir + sname
logging.info("Output prefix: " + outname)
exts = [".sa", ".amb", ".ann", ".pac", ".bwt"]
indexPresent = True
for i in exts:
if not os.path.exists(ref_fasta + i):
indexPresent = False
logging.info("Could not find " + ref_fasta + i + ", building BWA index from scratch. This could take > 60 minutes")
break
if not indexPresent:
cmd = "bwa index " + ref_fasta
call(cmd, shell=True)
print("\nPerforming alignment and sorting")
if usingDeprecatedSamtools:
cmd = "{{ bwa mem -K 10000000 -t {} {} {} | {} view -Shu - | {} sort -m 4G -@4 - {}.cs; }} 2>{}_aln_stage.stderr".format(
nthreads, ref_fasta, fastqs, samtools, samtools, outname, outname)
else:
cmd = "{{ bwa mem -K 10000000 -t {} {} {} | {} view -Shu - | {} sort -m 4G -@4 -o {}.cs.bam -; }} 2>{}_aln_stage.stderr".format(
nthreads, ref_fasta, fastqs, samtools, samtools, outname, outname)
logging.info(cmd)
call(cmd, shell=True)
metadata_dict["bwa_cmd"] = cmd
logging.info("\nPerforming duplicate removal & indexing")
cmd_list = [samtools, "rmdup", "-s", "{}.cs.bam".format(outname), "{}.cs.rmdup.bam".format(outname)]
# cmd_list = [samtools, "markdup", "-s", "-@ {}".format(nthreads), "{}.cs.bam".format(outname), {}.cs.rmdup.bam".format(outname)]
logging.info(" ".join(cmd_list))
call(cmd_list)
logging.info("\nRunning samtools index")
cmd_list = [samtools, "index", "{}.cs.rmdup.bam".format(outname)]
logging.info(" ".join(cmd_list))
call(cmd_list)
logging.info("Removing temp BAM")
cmd = "rm {}.cs.bam".format(outname)
call(cmd, shell=True)
return outname + ".cs.rmdup.bam", outname + "_aln_stage.stderr"
def run_freebayes(ref, bam_file, outdir, sname, nthreads, regions, fb_path=None):
# Freebayes cmd-line args
# -f is fasta
# -r is region to call
logging.info("Running freebayes...")
fb_exec = "freebayes"
if fb_path:
fb_exec = fb_path + "/" + fb_exec
while True:
try:
curr_region_tup = regions.pop()
except IndexError:
break
curr_region_string = curr_region_tup[0] + ":" + curr_region_tup[1]
logging.info(curr_region_string + ". " + str(len(regions)) + " items remaining.")
vcf_file = outdir + sname + "_" + curr_region_tup[0] + "_" + curr_region_tup[2] + ".vcf"
replace_filter_field_func = "awk '{ if (substr($1,1,1) != \"#\" ) { $7 = ($7 == \".\" ? \"PASS\" : $7 ) }} 1 ' OFS=\"\\t\""
cmd = "{} --genotype-qualities --standard-filters --use-best-n-alleles 5 --limit-coverage 25000 \
--strict-vcf -f {} -r {} {} | {} > {}".format(fb_exec, ref, curr_region_string, bam_file,
replace_filter_field_func, vcf_file)
logging.info(cmd)
call(cmd, shell=True)
# gzip the new VCF
call("gzip -f " + vcf_file, shell=True)
def run_cnvkit(ckpy_path, nthreads, outdir, bamfile, seg_meth='cbs', normal=None, ref_fasta=None, vcf=None):
# CNVkit cmd-line args
# -m wgs: wgs data
# -y: assume chrY present
# -n: create flat reference (cnv baseline)
# -p: number of threads
# -f: reference genome fasta
bamBase = os.path.splitext(os.path.basename(bamfile))[0]
cnvkit_version = Popen([PY3_PATH, ckpy_path, "version"], stdout=PIPE, stderr=PIPE).communicate()[0].rstrip()
try:
cnvkit_version = cnvkit_version.decode('utf-8')
except UnicodeError:
pass
metadata_dict["cnvkit_version"] = cnvkit_version
ckRef = AA_REPO + args.ref + "/" + args.ref + "_cnvkit_filtered_ref.cnn"
if normal and args.ref == "GRCh38_viral":
logging.warning("\nCNVkit does not properly support matched tumor-normal with viral genomes. Ignoring matched-"
"normal and running in tumor-only mode.")
logging.info("\nRunning CNVKit batch")
if normal and not args.ref == "GRCh38_viral":
# create a version of the stripped reference
scripts_dir = os.path.dirname(os.path.abspath(__file__)) + "/scripts/"
strip_cmd = "python {}reduce_fasta.py -r {} -c {} -o {}".format(scripts_dir, ref_fasta, ref_genome_size_file, outdir)
call(strip_cmd, shell=True)
base = os.path.basename(ref_fasta) # args.ref is the name, ref is the fasta
stripRefG = outdir + os.path.splitext(base)[0] + "_reduced" + "".join(os.path.splitext(base)[1:])
logging.debug("Stripped reference: " + stripRefG)
cmd = "{} {} batch {} -m wgs --fasta {} -p {} -d {} --normal {}".format(PY3_PATH, ckpy_path, bamfile, stripRefG,
nthreads, outdir, normal)
else:
cmd = "{} {} batch -m wgs -r {} -p {} -d {} {}".format(PY3_PATH, ckpy_path, ckRef, nthreads, outdir, bamfile)
logging.info(cmd)
call(cmd, shell=True)
metadata_dict["cnvkit_cmd"] = cmd + " ; "
rscript_str = ""
if args.rscript_path:
rscript_str = "--rscript-path " + args.rscript_path
logging.info("Set Rscript flag: " + rscript_str)
cnrFile = outdir + bamBase + ".cnr"
cnsFile = outdir + bamBase + ".cns"
logging.info("\nRunning CNVKit segment")
# TODO: possibly include support for adding VCF calls.
cmd = "{} {} segment {} {} -p {} -m {} -o {}".format(PY3_PATH, ckpy_path, cnrFile, rscript_str, nthreads, seg_meth,
cnsFile)
logging.info(cmd)
exit_code = call(cmd, shell=True)
if exit_code != 0:
logging.error("CNVKit encountered a non-zero exit status. Exiting...\n")
sys.exit(1)
metadata_dict["cnvkit_cmd"] = metadata_dict["cnvkit_cmd"] + cmd
logging.info("\nCleaning up temporary CNVkit files")
cmd = "rm -f {}/*tmp.bed {}/*.cnn {}/*target.bed {}/*.bintest.cns".format(outdir, outdir, outdir, outdir)
logging.info(cmd)
call(cmd, shell=True)
cmd = "gzip -f " + cnrFile
logging.info(cmd)
call(cmd, shell=True)
if normal and not args.ref == "GRCh38_viral":
cmd = "rm " + stripRefG + " " + stripRefG + ".fai"
logging.info(cmd)
call(cmd, shell=True)
def merge_and_filter_vcfs(chr_names, vcf_list, outdir, sname):
logging.info("\nMerging VCFs and zipping")
# collect the vcf files to merge
merged_vcf_file = outdir + sname + "_merged.vcf"
relevant_vcfs = [x for x in vcf_list if any([i in x for i in chr_names])]
chrom_vcf_d = {}
for f in relevant_vcfs:
curr_chrom = f.rsplit(".vcf.gz")[0].rsplit("_")[-2:]
chrom_vcf_d[curr_chrom[0] + curr_chrom[1]] = f
# chr_nums = [x.lstrip("chr") for x in chr_names]
pre_chr_str_names = [str(x) for x in range(1, 23)] + ["X", "Y"]
# sort the elements
# include the header from the first one
if args.ref != "GRCh37" and args.ref != "GRCm38":
sorted_chr_names = ["chr" + str(x) for x in pre_chr_str_names]
cmd = "zcat " + chrom_vcf_d["chrM"] + ''' | awk '$4 != "N"' > ''' + merged_vcf_file
else:
sorted_chr_names = [str(x) for x in pre_chr_str_names]
cmd = "zcat " + chrom_vcf_d["MT"] + ''' | awk '$4 != "N"' > ''' + merged_vcf_file
logging.info(cmd)
call(cmd, shell=True)
# zcat the rest, grepping out all header lines starting with "#"
logging.debug(sorted_chr_names)
for i in sorted_chr_names:
if i == "chrM" or i == "MT":
continue
cmd_p = "zcat " + chrom_vcf_d[i + "p"] + ''' | grep -v "^#" | awk '$4 != "N"' >> ''' + merged_vcf_file
cmd_q = "zcat " + chrom_vcf_d[i + "q"] + ''' | grep -v "^#" | awk '$4 != "N"' >> ''' + merged_vcf_file
logging.info(cmd_p)
call(cmd_p, shell=True)
logging.info(cmd_q)
call(cmd_q, shell=True)
cmd = "gzip -f " + merged_vcf_file
logging.info(cmd)
call(cmd, shell=True)
return merged_vcf_file + ".gz"
# Read the CNVkit .cns files
def convert_cnvkit_cns_to_bed(cnvkit_output_directory, base, cnsfile=None, rescaled=False, nofilter=False):
if cnsfile is None:
if not rescaled:
cnsfile = cnvkit_output_directory + base + ".cns"
else:
cnsfile = cnvkit_output_directory + base + "_rescaled.cns"
with open(cnsfile) as infile, open(cnvkit_output_directory + base + "_CNV_CALLS.bed", 'w') as outfile:
head = next(infile).rstrip().rsplit("\t")
for line in infile:
fields = line.rstrip().rsplit("\t")
# s, e = int(fields[1]), int(fields[2])
cn_r = float(fields[4])
cn = 2 ** (cn_r + 1)
# do not filter on size since amplified_intervals.py will merge small ones.
outline = "\t".join(fields[0:3] + ["CNVkit", str(cn)]) + "\n"
outfile.write(outline)
return cnvkit_output_directory + base + "_CNV_CALLS.bed"
def rescale_cnvkit_calls(ckpy_path, cnvkit_output_directory, base, cnsfile=None, ploidy=None, purity=None):
if purity is None and ploidy is None:
logging.warning("Warning: Rescaling called without --ploidy or --purity. Rescaling will have no effect.")
if cnsfile is None:
cnsfile = cnvkit_output_directory + base + ".cns"
if purity < 0.4:
logging.warning("WARNING! Rescaling a low purity sample may cause many false-positive seed regions!")
cmd = "{} {} call {} -m clonal".format(PY3_PATH, ckpy_path, cnsfile)
if purity:
cmd += " --purity " + str(purity)
if ploidy:
cmd += " --ploidy " + str(ploidy)
cmd += " -o " + cnvkit_output_directory + base + "_rescaled.cns"
logging.info("Rescaling CNVKit calls\n" + cmd)
call(cmd, shell=True)
def run_amplified_intervals(AA_interpreter, CNV_seeds_filename, sorted_bam, output_directory, sname, cngain,
cnsize_min):
logging.info("\nRunning amplified_intervals")
AA_seeds_filename = "{}_AA_CNV_SEEDS".format(output_directory + sname)
cmd = "amplified_intervals.py --ref {} --bed {} --bam {} --gain {} --cnsize_min {} --out {}".format(
args.ref, CNV_seeds_filename, sorted_bam, str(cngain), str(cnsize_min),
AA_seeds_filename)
logging.info(cmd)
exit_code = call(cmd, shell=True)
if exit_code != 0:
logging.error("amplified_intervals.py returned a non-zero exit code. Exiting...\n")
sys.exit(1)
metadata_dict["amplified_intervals_cmd"] = cmd
return AA_seeds_filename + ".bed"
def run_AA(amplified_interval_bed, AA_outdir, sname, args):
AA_interpreter = args.aa_python_interpreter
sorted_bam = args.bam
downsample = args.downsample
ref = args.ref
runmode = args.AA_runmode
extendmode = args.AA_extendmode
insert_sdevs = args.AA_insert_sdevs
sv_vcf = args.sv_vcf
sv_vcf_no_filter = args.sv_vcf_no_filter
AA_version = \
Popen([AA_interpreter, AA_SRC + "/AmpliconArchitect.py", "--version"], stdout=PIPE, stderr=PIPE).communicate()[
1].rstrip()
try:
AA_version = AA_version.decode('utf-8')
except UnicodeError:
pass
metadata_dict["AA_version"] = AA_version
cmd = "{} {}/AmpliconArchitect.py --ref {} --downsample {} --bed {} --bam {} --runmode {} --extendmode {} --out {}/{}".format(
AA_interpreter, AA_SRC, ref, str(downsample), amplified_interval_bed, sorted_bam, runmode, extendmode,
AA_outdir, sname)
if insert_sdevs is not None:
cmd += " --insert_sdevs {}".format(str(insert_sdevs))
if sv_vcf:
cmd += " --sv_vcf {}".format(sv_vcf)
if sv_vcf_no_filter:
cmd += " --sv_vcf_no_filter"
logging.info(cmd)
aa_exit_code = call(cmd, shell=True)
if aa_exit_code != 0:
logging.error("AmpliconArchitect returned a non-zero exit code. Exiting...\n")
sys.exit(1)
metadata_dict["AA_cmd"] = cmd
def run_AC(AA_outdir, sname, ref, AC_outdir, AC_src):
logging.info("\nRunning AC")
# make input file
class_output = AC_outdir + sname
input_file = class_output + ".input"
bed_dir = class_output + "_classification_bed_files/"
if os.path.exists(bed_dir):
logging.warning("WARNING! AC files were not cleared prior to re-running. New classifications may become "
"mixed with previous classification files!")
cmd = "{}/make_input.sh {} {}".format(AC_src, AA_outdir, class_output)
logging.info(cmd)
call(cmd, shell=True)
with open(input_file) as ifile:
sample_info_dict["number_of_AA_amplicons"] = len(ifile.readlines())
cmd = "{} {}/amplicon_classifier.py -i {} --ref {} -o {} --report_complexity".format(PY3_PATH, AC_src, input_file,
ref, class_output)
logging.info(cmd)
call(cmd, shell=True)
metadata_dict["AC_cmd"] = cmd
# Get AC version
AC_version = \
Popen([PY3_PATH, AC_src + "/amplicon_classifier.py", "--version"], stdout=PIPE, stderr=PIPE).communicate()[
0].rstrip()
try:
AC_version = AC_version.decode('utf-8')
except UnicodeError:
pass
metadata_dict["AC_version"] = AC_version
# iterate over the bed files and count anything that isn't "unknown" as a feature
feat_count = 0
if os.path.exists(bed_dir):
for bf in os.listdir(bed_dir):
if not "unknown" in bf and bf.endswith(".bed"):
feat_count += 1
sample_info_dict["number_of_AA_features"] = feat_count
def make_AC_table(sname, AC_outdir, AC_src, run_metadata_file, sample_metadata_file, cnv_bed=None):
# make the AC output table
class_output = AC_outdir + sname
input_file = class_output + ".input"
summary_map_file = class_output + "_summary_map.txt"
classification_file = class_output + "_amplicon_classification_profiles.tsv"
cmd = "{} {}/make_results_table.py -i {} --classification_file {} --summary_map {}".format(
PY3_PATH, AC_src, input_file, classification_file, summary_map_file)
if cnv_bed:
cmd += " --cnv_bed " + cnv_bed
if run_metadata_file:
cmd += " --run_metadata_file " + run_metadata_file
if sample_metadata_file:
cmd += " --sample_metadata_file " + sample_metadata_file
logging.info(cmd)
call(cmd, shell=True)
def get_ref_sizes(ref_genome_size_file):
chr_sizes = {}
with open(ref_genome_size_file) as infile:
for line in infile:
fields = line.rstrip().rsplit()
if fields:
chr_sizes[fields[0]] = str(int(fields[1]) - 1)
return chr_sizes
def get_ref_centromeres(ref_name):
centromere_dict = {}
fnameD = {"GRCh38": "GRCh38_centromere.bed", "GRCh37": "human_g1k_v37_centromere.bed",
"hg19": "hg19_centromere.bed",
"mm10": "mm10_centromere.bed", "GRCm38": "GRCm38_centromere.bed", "GRCh38_viral": "GRCh38_centromere.bed"}
with open(AA_REPO + ref_name + "/" + fnameD[ref_name]) as infile:
for line in infile:
if not "centromere" in line and not "acen" in line:
continue
fields = line.rstrip().rsplit("\t")
if fields[0] not in centromere_dict:
centromere_dict[fields[0]] = (fields[1], fields[2])
else:
pmin = min(int(centromere_dict[fields[0]][0]), int(fields[1]))
pmax = max(int(centromere_dict[fields[0]][1]), int(fields[2]))
# pad with 20kb to avoid freebayes issues in calling near centromeres
centromere_dict[fields[0]] = (str(pmin - 20000), str(pmax + 20000))
return centromere_dict
def save_run_metadata(outdir, sname, args, launchtime, commandstring):
# make a dictionary that stores
# datetime
# hostname
# ref
# PAA command
# AA python interpreter version
# bwa cmd
# CN cmd
# AA cmd
# PAA version
# CNVKit version
# AA version
# AC version
metadata_dict["launch_datetime"] = launchtime
metadata_dict["hostname"] = socket.gethostname()
metadata_dict["ref_genome"] = args.ref
aapint = args.aa_python_interpreter if args.aa_python_interpreter else "python"
aa_python_v = Popen([aapint, "--version"], stdout=PIPE, stderr=PIPE).communicate()[1].rstrip()
try:
aa_python_v = aa_python_v.decode('utf-8')
except UnicodeError:
pass
metadata_dict["AA_python_version"] = aa_python_v
metadata_dict["PAA_command"] = commandstring
metadata_dict["PAA_version"] = __version__
for x in ["bwa_cmd", "cnvkit_cmd", "amplified_intervals_cmd", "AA_cmd", "AC_cmd", "cnvkit_version", "AA_version",
"AC_version"]:
if x not in metadata_dict:
metadata_dict[x] = "NA"
# save the json dict
run_metadata_filename = outdir + sname + "_run_metadata.json"
with open(run_metadata_filename, 'w') as fp:
json.dump(metadata_dict, fp, indent=2)
# sample_info_dict["run_metadata_file"] = run_metadata_filename
return run_metadata_filename
def detect_run_failure(align_stderr_file, AA_outdir, sname, AC_outdir):
if align_stderr_file:
cmd = 'grep -i error ' + align_stderr_file
try:
aln_errs = check_output(cmd, shell=True).decode("utf-8")
except CalledProcessError:
aln_errs = ""
if aln_errs:
logging.error("Detected error during bwa mem alignment stage\n")
return True
if AA_outdir:
sumfile = AA_outdir + sname + "_summary.txt"
if os.path.isfile(sumfile):
namps = -1
with open(sumfile) as infile:
for line in infile:
if line.startswith("#Amplicons = "):
namps = int(line.rstrip().rsplit(" = ")[-1])
break
if namps < 0:
logging.error("Detected truncated or missing AA outputs")
return True
for x in range(1, namps + 1):
try:
fsize = os.stat(AA_outdir + sname + "_amplicon" + str(x) + "_cycles.txt").st_size
except OSError:
fsize = 0
if fsize == 0:
logging.error("Detected truncated or missing AA outputs")
return True
else:
logging.error("Detected error during AA stage")
return True
if AC_outdir:
try:
fsize1 = os.stat(AC_outdir + sname + "_amplicon_classification_profiles.tsv").st_size
fsize2 = os.stat(AC_outdir + sname + "_result_table.tsv").st_size
except OSError:
fsize1 = 0
fsize2 = 0
if fsize1 == 0 or fsize2 == 0:
logging.error("Detected error during AC stage\n")
return True
return False
def download_file(url, destination_folder):
filename = os.path.join(destination_folder, url.split("/")[-1])
try:
response = urllib.request.urlopen(url)
file_size = int(response.headers.get('Content-Length', 0))
response.close()
file_size = round(file_size / (1024**3), 2)
if file_size > 0.1:
print("\nDownloading " + url + " ... (" + str(file_size) + "GB)")
else:
print("\nDownloading " + url + " ...")
urllib.request.urlretrieve(url, filename)
print("File downloaded and saved to: " + str(filename))
except Exception as e:
print("Failed to download file. Error: " + str(e))
def extract_tar_gz(file_path, destination_folder):
if not file_path.endswith('.tar.gz'):
sys.stderr.write("Cannot extract file " + file_path)
sys.exit(1)
with tarfile.open(file_path, 'r:gz') as tar:
tar.extractall(destination_folder)
os.remove(file_path)
# MAIN #
if __name__ == '__main__':
# Parses the command line arguments
parser = argparse.ArgumentParser(
description="A pipeline wrapper for AmpliconArchitect, invoking alignment CNV calling and CNV filtering prior. "
"Can launch AA, as well as downstream amplicon classification.")
parser.add_argument("-v", "--version", action='version',
version='AmpliconSuite-pipeline version {version} \n'.format(version=__version__))
parser.add_argument("--download_repo", help="Download the selected data repo to the $AA_DATA_REPO "
"directory and exit. '_indexed' suffix indicates BWA index is included, which is useful if "
"performing alignment with AmpliconSuite-pipeline, but has a larger filesize.", choices=["hg19",
"GRCh37", "GRCh38", "mm10", "GRCh38_viral", "hg19_indexed", "GRCh37_indexed", "GRCh38_indexed",
"mm10_indexed", "GRCh38_viral_indexed"], nargs='+')
parser.add_argument("-o", "--output_directory", metavar='PATH', help="output directory names (will create if not already created)")
parser.add_argument("-s", "--sample_name", metavar='STR', help="(Required) Sample name")
parser.add_argument("-t", "--nthreads", metavar='INT', help="(Required) Number of threads to use in BWA and CNV calling")
parser.add_argument("--run_AA", help="Run AA after all files prepared. Default off.", action='store_true')
parser.add_argument("--run_AC", help="Run AmpliconClassifier after all files prepared. Default off.",
action='store_true')
parser.add_argument("--ref", metavar='STR', help="Reference genome version.", choices=["hg19", "GRCh37",
"GRCh38", "hg38", "mm10", "GRCm38", "GRCh38_viral"])
parser.add_argument("--cngain", metavar='FLOAT', type=float, help="CN gain threshold to consider for AA seeding",
default=4.5)
parser.add_argument("--cnsize_min", metavar='INT', type=int, help="CN interval size (in bp) to consider for AA seeding",
default=50000)
parser.add_argument("--downsample", metavar='FLOAT', type=float, help="AA downsample argument (see AA documentation)",
default=10)
parser.add_argument("--use_old_samtools", help="Indicate you are using an old build of samtools prior to version 1.0",
action='store_true', default=False)
parser.add_argument("--rscript_path", metavar='PATH', help="Specify custom path to Rscript for CNVKit, "
"which requires R version >=3.5")
parser.add_argument("--python3_path", metavar='PATH', help="If needed, specify a custom path to python3.")
parser.add_argument("--aa_python_interpreter",
help="By default AmpliconSuite-pipeline will use the system's default python path. If you would like to use "
"a different python version with AA, set this to either the path to the interpreter or "
"'python3' or 'python2'", metavar='PATH', type=str, default='python')
parser.add_argument("--sv_vcf",
help="Provide a VCF file of externally-called SVs to augment SVs identified by AA internally.",
metavar='FILE', action='store', type=str)
parser.add_argument("--sv_vcf_no_filter", help="Use all external SV calls from the --sv_vcf arg, even "
"those without 'PASS' in the FILTER column.", action='store_true', default=False)
parser.add_argument("--AA_src", metavar='PATH', help="Specify a custom $AA_SRC path. Overrides the bash variable")
parser.add_argument("--AA_runmode", metavar='STR', help="If --run_AA selected, set the --runmode argument to AA. Default mode is "
"'FULL'", choices=['FULL', 'BPGRAPH', 'CYCLES', 'SVVIEW'], default='FULL')
parser.add_argument("--AA_extendmode", metavar='STR', help="If --run_AA selected, set the --extendmode argument to AA. Default "
"mode is 'EXPLORE'", choices=["EXPLORE", "CLUSTERED", "UNCLUSTERED", "VIRAL"], default='EXPLORE')
parser.add_argument("--AA_insert_sdevs", help="Number of standard deviations around the insert size. May need to "
"increase for sequencing runs with high variance after insert size selection step. (default "
"3.0)", metavar="FLOAT", type=float, default=None)
parser.add_argument("--normal_bam", metavar='FILE', help="Path to matched normal bam for CNVKit (optional)")
parser.add_argument("--ploidy", metavar='FLOAT', type=float, help="Ploidy estimate for CNVKit (optional). This is not used outside of CNVKit.",
default=None)
parser.add_argument("--purity", metavar='FLOAT', type=float, help="Tumor purity estimate for CNVKit (optional). This is not used outside of CNVKit.",
default=None)
parser.add_argument("--cnvkit_segmentation", metavar='STR', help="Segmentation method for CNVKit (if used), defaults to CNVKit "
"default segmentation method (cbs).", choices=['cbs', 'haar', 'hmm', 'hmm-tumor', 'hmm-germline', 'none'],
default='cbs')
parser.add_argument("--no_filter", help="Do not run amplified_intervals.py to identify amplified seeds",
action='store_true')
parser.add_argument("--no_QC", help="Skip QC on the BAM file. Do not adjust AA insert_sdevs for "
"poor-quality insert size distribution", action='store_true')
parser.add_argument("--sample_metadata", metavar='FILE', help="JSON file of sample metadata to build on")
parser.add_argument("--samtools_path", help="Path to samtools binary (e.g., /path/to/my/samtools). If unset, will use samtools on system path.",
default='')
group = parser.add_mutually_exclusive_group()
group.add_argument("--bam", "--sorted_bam", metavar='FILE', help="Coordinate sorted BAM file (aligned to an AA-supported "
"reference.)")
group.add_argument("--fastqs", metavar='TWO FILES', help="Fastq files (r1.fq r2.fq)", nargs=2)
group.add_argument("--completed_AA_runs", metavar='PATH',
help="Path to a directory containing one or more completed AA runs which utilized the same reference genome.")
group2 = parser.add_mutually_exclusive_group()
group2.add_argument("--cnv_bed", "--bed", metavar='FILE',
help="BED file (or CNVKit .cns file) of CNV changes. Fields in the bed file should"
" be: chr start end name cngain")
group2.add_argument("--cnvkit_dir", metavar='PATH', help="Path to cnvkit.py. Assumes CNVKit is on the system path if not set",
default="")
group2.add_argument("--completed_run_metadata", metavar='FILE',
help="Run metadata JSON to retroactively assign to collection of samples", default="")
group2.add_argument("--align_only", help="Only perform the alignment stage (do not run CNV calling and seeding",
action='store_true')
# start timing
ta = time.time()
ti = ta
launchtime = str(datetime.now())
args = parser.parse_args()
# Check if AA_REPO set, print error and quit if not
try:
AA_REPO = os.environ['AA_DATA_REPO'] + "/"
except KeyError:
sys.stderr.write("AA_DATA_REPO bash variable not found. Please see installation instructions and run ./install.sh before using.\n")
sys.exit(1)
# Download any requested data repo files
if args.download_repo:
# launch data repo download and exit
data_repo_base_url = "https://datasets.genepattern.org/data/module_support_files/AmpliconArchitect/"
for ref in args.download_repo:
print(ref)
ref_base_url = data_repo_base_url + ref
md5file = ref_base_url + "_md5sum.txt"
ref_file = ref_base_url + ".tar.gz"
if os.path.exists(AA_REPO + ref):
print("An AA data repo directory already exists for " + ref + " and it will be replaced!")
download_file(md5file, AA_REPO)
download_file(ref_file, AA_REPO)
print("Extracting...\n")
extract_tar_gz(AA_REPO + ref + ".tar.gz", AA_REPO)
print("Finished")
sys.exit(0)
# Preflight checks for running AS-pipeline
if not args.sample_name:
parser.error("--sample_name (-s) is a required argument.")
if not args.nthreads:
parser.error("--nthreads (-t) is a required argument.")
if not any([args.bam, args.fastqs, args.completed_AA_runs]):
parser.error("One of --bam | --fastqs | --completed_AA_runs is required!")
# set an output directory if user did not specify
if not args.output_directory:
args.output_directory = os.getcwd()
if not args.output_directory.endswith("/"):
args.output_directory += "/"
sname = args.sample_name
outdir = args.output_directory
sample_metadata_filename = args.output_directory + sname + "_sample_metadata.json"
# set samtools version for use
if not args.samtools_path.endswith("/samtools"):
if args.samtools_path and not args.samtools_path.endswith("/"):
args.samtools_path += "/"
args.samtools_path += "samtools"
# Make and clear necessary directories.
# make the output directory location if it does not exist
if not os.path.exists(args.output_directory):
os.mkdir(args.output_directory)
# initiate logging
paa_logfile = args.output_directory + sname + '.log'
logging.basicConfig(filename=paa_logfile, format='[%(name)s:%(levelname)s]\t%(message)s',
level=logging.INFO)
logging.getLogger().addHandler(logging.StreamHandler())
logging.info("Launched on " + launchtime)
logging.info("AmpiconSuite-pipeline version " + __version__ + "\n")
commandstring = ""
for arg in sys.argv:
if ' ' in arg:
commandstring += '"{}" '.format(arg)
else:
commandstring += "{} ".format(arg)
logging.info(commandstring + "\n")
if "/" in args.sample_name:
logging.error("Sample name -s cannot be a path. Specify output directory with -o.\n")
sys.exit(1)
finish_flag_filename = args.output_directory + args.sample_name + "_finish_flag.txt"
if os.path.exists(finish_flag_filename):
logging.warning("WARNING: Running AmpliconSuite-pipeline.py with outputs directed into the same output location"
" as a previous run may cause crashes or other unexpected behavior. To avoid errors, clear "
"previous files before re-running.\n")
with open(finish_flag_filename, 'w') as ffof:
ffof.write("UNSUCCESSFUL\n")
timing_logfile = open(args.output_directory + args.sample_name + '_timing_log.txt', 'w')
timing_logfile.write("#stage:\twalltime(seconds)\n")
# Check if expected system paths and files are present. Check if provided argument combinations are valid.
if args.AA_src:
os.environ['AA_SRC'] = args.AA_src
if not os.path.exists(os.path.join(AA_REPO, "coverage.stats")):
logging.info("coverage.stats file not found in " + AA_REPO + "\nCreating a new coverage.stats file.")
cmd = "touch {}coverage.stats && chmod a+rw {}coverage.stats".format(AA_REPO, AA_REPO)
logging.info(cmd)
call(cmd, shell=True)
try:
AA_SRC = os.environ['AA_SRC']
except KeyError:
try:
import ampliconarchitectlib
AA_SRC = os.path.realpath(os.path.dirname(ampliconarchitectlib.__file__))
except ModuleNotFoundError:
logging.error("AA_SRC bash variable or library files not found. AmpliconArchitect may not be properly installed.\n")
sys.exit(1)
try:
AC_SRC = os.environ['AC_SRC']
except KeyError:
try:
import ampclasslib
ac_path = check_output("which amplicon_classifier.py", shell=True).decode("utf-8")
AC_SRC = ac_path.rsplit("/amplicon_classifier.py")[0]
except Exception as e:
logging.error(e)
logging.error(
"\nAC_SRC bash variable or library files not found. AmpliconClassifier may not be properly installed.\n")
sys.exit(1)
if (args.fastqs or args.completed_AA_runs) and not args.ref:
logging.error("Must specify --ref when providing unaligned fastq files or completed AA runs.\n")
sys.exit(1)
if args.completed_run_metadata.lower() == "none":
args.completed_run_metadata = None
# if not these args are set, assume cnvkit.py is on the path.
if not (args.cnv_bed or args.cnvkit_dir or args.completed_run_metadata or args.align_only) and (args.fastqs or
args.bam):
try:
args.cnvkit_dir = str(check_output(["which cnvkit.py"], shell=True).decode("utf-8").rstrip())
except CalledProcessError:
logging.error("cnvkit.py not found on system path. Must specify --cnvkit_dir")
sys.exit(1)
elif args.cnvkit_dir and not args.cnvkit_dir.endswith("/") and not args.cnvkit_dir.endswith("cnvkit.py"):
args.cnvkit_dir += "/"
else:
args.completed_run_metadata = None
if not args.cnvkit_dir.endswith("cnvkit.py"):
args.cnvkit_dir += "cnvkit.py"
if args.run_AA:
if not os.path.exists(os.environ["HOME"] + "/mosek/mosek.lic") and not "MOSEKLM_LICENSE_FILE" in os.environ:
logging.error("--run_AA set, but MOSEK license not found!")
sys.exit(1)
elif "MOSEKLM_LICENSE_FILE" in os.environ and not os.path.exists(os.environ["MOSEKLM_LICENSE_FILE"] + "/mosek.lic"):
logging.error("--run_AA set, but MOSEK license not found!")
sys.exit(1)
runCNV = None
if args.cnvkit_dir and not args.cnv_bed:
runCNV = "CNVkit"
# check Rscript version
test_rscript = "Rscript"
if args.rscript_path:
if not args.rscript_path.endswith("/Rscript"):
args.rscript_path += "/Rscript"
test_rscript = args.rscript_path
try:
rscript_version_out = str(check_output([test_rscript, "--version"], stderr=STDOUT).decode("utf-8").rstrip())
except CalledProcessError:
logging.error(test_rscript + " not found. Must specify --rscript_path")
sys.exit(1)
if args.python3_path:
if not args.python3_path.endswith("/python") and not args.python3_path.endswith("/python3"):
args.python3_path += "/python3"
PY3_PATH = args.python3_path
refFnames = {x: None for x in ["hg19", "GRCh37", "GRCh38", "GRCh38_viral", "mm10"]}
# Paths of all the repo files needed
if args.ref == "hg38":
args.ref = "GRCh38"
if args.ref == "GRCm38":
args.ref = "mm10"
for rname in refFnames.keys():
if os.path.exists(AA_REPO + "/" + rname):
refFnames[rname] = check_reference.get_ref_fname(AA_REPO, rname)
faidict = {}
"""
if args.bam:
if args.ref and refFnames[args.ref]:
faidict[args.ref] = AA_REPO + args.ref + "/" + refFnames[args.ref] + ".fai"
elif args.ref and refFnames[args.ref] is None:
em = "Data repo files for ref " + args.ref + " not found. Please download using the '--download_repo " + args.ref + "' option\n"
logging.error(em)
sys.exit(1)
else:
for k, v in refFnames.items():
if v:
faidict[k] = AA_REPO + k + "/" + v + ".fai"
determined_ref = check_reference.check_ref(args.bam, faidict, args.samtools_path)
if not determined_ref and not args.ref:
logging.error("Could not determine ref build. Please make sure AA data repo is populated.")
sys.exit(1)
elif not args.ref:
args.ref = determined_ref
elif args.ref and not determined_ref:
logging.warning("WARNING! The BAM file did not match " + args.ref)
try:
with open(AA_REPO + args.ref + "/last_updated.txt", 'r') as file:
datestring = file.read()
logging.info(args.ref + " data repo constructed on " + datestring)
except FileNotFoundError:
logging.warning("Data repo appears to be out of date. Please update your data repo!\n")
"""
gdir = AA_REPO + args.ref + "/"
ref_fasta = gdir + refFnames[args.ref]
ref_genome_size_file = gdir + args.ref + "_noAlt.fa.fai"
if args.cnv_bed and not os.path.isfile(args.cnv_bed):
logging.error("Specified CNV bed file does not exist: " + args.cnv_bed + "\n")
sys.exit(1)
if not args.sample_metadata:
args.sample_metadata = os.path.realpath(os.path.dirname(check_reference.__file__)) + "/sample_metadata_skeleton.json"
with open(args.sample_metadata) as input_json:
sample_info_dict = json.load(input_json)
sample_info_dict["reference_genome"] = args.ref
sample_info_dict["sample_name"] = sname
tb = time.time()
timing_logfile.write("Initialization:\t" + "{:.2f}".format(tb - ta) + "\n")
ta = tb
logging.info("Running AmpliconSuite-pipeline on sample: " + sname)
# Begin pipeline
aln_stage_stderr = None
if args.fastqs:
# Run BWA
fastqs = " ".join(args.fastqs)
logging.info("Will perform alignment on " + fastqs)
args.bam, aln_stage_stderr = run_bwa(ref_fasta, fastqs, outdir, sname, args.nthreads, args.samtools_path, args.use_old_samtools)
if not args.completed_AA_runs:
bamBaiNoExt = args.bam[:-3] + "bai"
cramCraiNoExt = args.bam[:-4] + "crai"
baiExists = os.path.isfile(args.bam + ".bai") or os.path.isfile(bamBaiNoExt)
craiExists = os.path.isfile(args.bam + ".crai") or os.path.isfile(cramCraiNoExt)
if not baiExists and not craiExists:
logging.info(args.bam + " index not found, calling samtools index")
call([args.samtools_path, "index", args.bam])
logging.info("Finished indexing")
bambase = os.path.splitext(os.path.basename(args.bam))[0]
prop_paired_proportion = None
if not args.no_QC:
logging.debug("samtools path is set to: " + args.samtools_path)
prop_paired_proportion = check_reference.check_properly_paired(args.bam, args.samtools_path)
tb = time.time()
timing_logfile.write("Alignment, indexing and QC:\t" + "{:.2f}".format(tb - ta) + "\n")
if args.align_only:
logging.info("Completed\n")
tf = time.time()
timing_logfile.write("Total_elapsed_walltime\t" + "{:.2f}".format(tf - ti) + "\n")
timing_logfile.close()
sys.exit()
ta = tb
centromere_dict = get_ref_centromeres(args.ref)
chr_sizes = get_ref_sizes(ref_genome_size_file)
# coordinate CNV calling
if runCNV == "CNVkit":
cnvkit_output_directory = args.output_directory + sname + "_cnvkit_output/"
if not os.path.exists(cnvkit_output_directory):
os.mkdir(cnvkit_output_directory)
run_cnvkit(args.cnvkit_dir, args.nthreads, cnvkit_output_directory, args.bam,
seg_meth=args.cnvkit_segmentation, normal=args.normal_bam, ref_fasta=ref_fasta)
if args.ploidy or args.purity:
rescale_cnvkit_calls(args.cnvkit_dir, cnvkit_output_directory, bambase, ploidy=args.ploidy,
purity=args.purity)
rescaling = True
else:
rescaling = False
args.cnv_bed = convert_cnvkit_cns_to_bed(cnvkit_output_directory, bambase, rescaled=rescaling)
if args.cnv_bed.endswith(".cns"):
args.cnv_bed = convert_cnvkit_cns_to_bed(outdir, bambase, cnsfile=args.cnv_bed, nofilter=True)
tb = time.time()
timing_logfile.write("CNV calling:\t" + "{:.2f}".format(tb - ta) + "\n")
ta = tb
sample_info_dict["sample_cnv_bed"] = args.cnv_bed
if not args.no_filter and not args.cnv_bed.endswith("_AA_CNV_SEEDS.bed"):
if not args.cnv_bed.endswith("_CNV_CALLS_pre_filtered.bed"):
args.cnv_bed = cnv_prefilter.prefilter_bed(args.cnv_bed, args.ref, centromere_dict, chr_sizes,
args.cngain, args.output_directory)
amplified_interval_bed = run_amplified_intervals(args.aa_python_interpreter, args.cnv_bed, args.bam,
outdir, sname, args.cngain, args.cnsize_min)
elif args.no_filter and runCNV:
if not args.cnv_bed.endswith("_CNV_CALLS_pre_filtered.bed"):
args.cnv_bed = cnv_prefilter.prefilter_bed(args.cnv_bed, args.ref, centromere_dict, chr_sizes,
args.cngain, args.output_directory)
logging.info("Skipping amplified_intervals.py step due to --no_filter")
else:
logging.info("Skipping filtering of bed file.")
amplified_interval_bed = args.cnv_bed
tb = time.time()
timing_logfile.write("Seed filtering (amplified_intervals.py):\t" + "{:.2f}".format(tb - ta) + "\n")
ta = tb
# Run AA
if args.run_AA:
AA_outdir = outdir + sname + "_AA_results/"
if not os.path.exists(AA_outdir):
os.mkdir(AA_outdir)
# set the insert sdevs if not given by user.
if not args.no_QC and not args.AA_insert_sdevs and prop_paired_proportion is not None and prop_paired_proportion < 90:
logging.info("Properly paired rate less than 90%, setting --insert_sdevs 9.0 for AA")
args.AA_insert_sdevs = 9.0
run_AA(amplified_interval_bed, AA_outdir, sname, args)
tb = time.time()
timing_logfile.write("AmpliconArchitect:\t" + "{:.2f}".format(tb - ta) + "\n")
ta = tb
# Run AC
if args.run_AC:
AC_outdir = outdir + sname + "_classification/"
if not os.path.exists(AC_outdir):
os.mkdir(AC_outdir)
run_AC(AA_outdir, sname, args.ref, AC_outdir, AC_SRC)
tb = time.time()
timing_logfile.write("AmpliconClassifier:\t" + "{:.2f}".format(tb - ta) + "\n")
#run_metadata_filename = save_run_metadata(outdir, sname, args, launchtime, commandstring)
#with open(sample_metadata_filename, 'w') as fp:
# json.dump(sample_info_dict, fp, indent=2)
#if args.run_AA and args.run_AC:
# make_AC_table(sname, AC_outdir, AC_SRC, run_metadata_filename, sample_metadata_filename,
# sample_info_dict["sample_cnv_bed"])
else:
ta = time.time()