def main():
'''
Organization function
-setups logging
-gets inputdata
-calls plotting function
'''
args = get_args()
sources = {
"fastq": args.fastq,
"bam": args.bam,
"cram": args.cram,
"fastq_rich": args.fastq_rich,
"fastq_minimal": args.fastq_minimal,
"summary": args.summary,
"fasta": args.fasta,
"ubam": args.ubam,
}
get_input(
source=[n for n, s in sources.items() if s][0],
files=[f for f in sources.values() if f][0],
threads=args.threads,
readtype=args.readtype,
combine="simple",
barcoded=args.barcoded,
huge=args.huge,
keep_supp=not(args.no_supplementary)) \
.to_feather(args.output)
def main():
args = get_args()
if args.outdir and not os.path.exists(args.outdir):
os.makedirs(args.outdir)
if args.feather:
from nanoget import combine_dfs
from pandas import read_feather
datadf = combine_dfs([read_feather(p) for p in args.feather],
method="simple")
else:
sources = {
"fastq": args.fastq,
"bam": args.bam,
"cram": args.cram,
"summary": args.summary,
"fasta": args.fasta,
"ubam": args.ubam,
}
datadf = nanoget.get_input(source=[n for n, s in sources.items()
if s][0],
files=[f for f in sources.values() if f][0],
threads=args.threads,
readtype=args.readtype,
combine="track",
barcoded=args.barcoded,
keep_supp=not (args.no_supplementary))
if args.barcoded:
barcodes = list(datadf["barcode"].unique())
write_stats(datadfs=[datadf[datadf["barcode"] == b] for b in barcodes],
outputfile=os.path.join(args.outdir, args.name),
names=barcodes)
write_stats(datadfs=[datadf],
outputfile=os.path.join(args.outdir, args.name),
as_tsv=args.tsv)
def main():
args = get_args()
merged_df = get_input(source="summary", files=args.summary).set_index("readIDs") \
.merge(right=get_input(source="bam", files=args.bam).set_index("readIDs"),
how="left",
left_index=True,
right_index=True)
plot_retrotect(df=merged_df,
path=path.join(args.outdir, args.prefix),
figformat=args.format,
title=args.title,
hours=args.hours)
merged_df.dropna(axis="index", how="any").sort_values(by="start_time").to_csv(
path_or_buf=path.join(args.outdir, args.prefix) + "Retrotect_details.txt.gz",
sep="\t",
columns=["start_time"],
compression='gzip')
def main():
'''
Organization function
-setups logging
-gets inputdata
-calls plotting function
'''
settings, args = utils.get_args()
try:
utils.make_output_dir(args.outdir)
utils.init_logs(args)
args.format = utils.check_valid_format(args.format)
sources = {
"fastq": args.fastq,
"bam": args.bam,
"cram": args.cram,
"summary": args.summary,
"fasta": args.fasta,
"ubam": args.ubam,
}
if args.split_runs:
split_dict = utils.validate_split_runs_file(args.split_runs)
datadf = nanoget.get_input(source=[n for n, s in sources.items()
if s][0],
files=[f for f in sources.values() if f][0],
threads=args.threads,
readtype=args.readtype,
names=args.names,
barcoded=args.barcoded,
combine="track")
datadf, settings = filter_and_transform_data(datadf, vars(args))
if args.raw:
datadf.to_csv(settings["path"] + "NanoComp-data.tsv.gz",
sep="\t",
index=False,
compression="gzip")
if args.store:
pickle.dump(obj=datadf,
file=open(settings["path"] + "NanoComp-data.pickle",
'wb'))
if args.split_runs:
utils.change_identifiers(datadf, split_dict)
if args.barcoded:
datadf["dataset"] = datadf["barcode"]
identifiers = list(datadf["dataset"].unique())
write_stats(
datadfs=[datadf[datadf["dataset"] == i] for i in identifiers],
outputfile=settings["path"] + "NanoStats.txt",
names=identifiers)
if args.plot != 'false':
plots = make_plots(datadf, settings)
make_report(plots, settings["path"])
logging.info("Succesfully processed all input.")
except Exception as e:
logging.error(e, exc_info=True)
raise
def main():
'''
Organization function
-setups logging
-gets inputdata
-calls plotting function
'''
args = get_args()
try:
utils.make_output_dir(args.outdir)
utils.init_logs(args, tool="NanoComp")
args.format = nanoplotter.check_valid_format(args.format)
settings = vars(args)
settings["path"] = path.join(args.outdir, args.prefix)
sources = [args.fastq, args.bam, args.summary, args.fasta]
sourcename = ["fastq", "bam", "summary", "fasta"]
if args.split_runs:
split_dict = validate_split_runs_file(args.split_runs)
datadf = nanoget.get_input(
source=[n for n, s in zip(sourcename, sources) if s][0],
files=[f for f in sources if f][0],
threads=args.threads,
readtype=args.readtype,
names=args.names,
barcoded=args.barcoded,
combine="track")
if args.raw:
datadf.to_csv("NanoComp-data.tsv.gz",
sep="\t",
index=False,
compression="gzip")
if args.split_runs:
change_identifiers(datadf, split_dict)
if args.barcoded:
datadf["dataset"] = datadf["barcode"]
identifiers = list(datadf["dataset"].unique())
write_stats(
datadfs=[datadf[datadf["dataset"] == i] for i in identifiers],
outputfile=settings["path"] + "NanoStats.txt",
names=identifiers)
plots = make_plots(datadf, settings)
make_report(plots, path.join(args.outdir, args.prefix))
logging.info("Succesfully processed all input.")
except Exception as e:
logging.error(e, exc_info=True)
raise
def main():
args = get_args()
if not os.path.exists(args.outdir):
os.makedirs(args.outdir)
sources = [args.fastq, args.bam, args.summary]
sourcename = ["fastq", "bam", "summary"]
datadf = nanoget.get_input(
source=[n for n, s in zip(sourcename, sources) if s][0],
files=[f for f in sources if f][0],
threads=args.threads,
readtype=args.readtype,
combine="track")
if args.name:
output = args.name
else:
output = os.path.join(args.outdir, args.prefix + "NanoStats.txt")
write_stats([datadf], output)
def main():
args = get_args()
if not os.path.exists(args.outdir):
os.makedirs(args.outdir)
sources = [args.fastq, args.bam, args.summary, args.fasta]
sourcename = ["fastq", "bam", "summary", "fasta"]
datadf = nanoget.get_input(
source=[n for n, s in zip(sourcename, sources) if s][0],
files=[f for f in sources if f][0],
threads=args.threads,
readtype=args.readtype,
combine="track",
barcoded=args.barcoded)
if args.barcoded:
barcodes = list(datadf["barcode"].unique())
write_stats(datadfs=[datadf[datadf["barcode"] == b] for b in barcodes],
outputfile=args.name,
names=barcodes)
write_stats(datadfs=[datadf], outputfile=args.name)
def main():
'''
Organization function
-setups logging
-gets inputdata
-calls plotting function
'''
settings, args = utils.get_args()
try:
utils.make_output_dir(args.outdir)
utils.init_logs(args)
args.format = nanoplotter.check_valid_format(args.format)
sources = {
"fastq": args.fastq,
"bam": args.bam,
"cram": args.cram,
"fastq_rich": args.fastq_rich,
"fastq_minimal": args.fastq_minimal,
"summary": args.summary,
"fasta": args.fasta,
"ubam": args.ubam,
}
if args.pickle:
datadf = pickle.load(open(args.pickle, 'rb'))
else:
datadf = get_input(source=[n for n, s in sources.items() if s][0],
files=[f for f in sources.values() if f][0],
threads=args.threads,
readtype=args.readtype,
combine="simple",
barcoded=args.barcoded,
huge=args.huge)
if args.store:
pickle.dump(obj=datadf,
file=open(settings["path"] + "NanoPlot-data.pickle",
'wb'))
if args.raw:
datadf.to_csv(settings["path"] + "NanoPlot-data.tsv.gz",
sep="\t",
index=False,
compression="gzip")
settings["statsfile"] = [make_stats(datadf, settings, suffix="")]
datadf, settings = filter_and_transform_data(datadf, settings)
if settings[
"filtered"]: # Bool set when filter was applied in filter_and_transform_data()
settings["statsfile"].append(
make_stats(datadf[datadf["length_filter"]],
settings,
suffix="_post_filtering"))
if args.barcoded:
barcodes = list(datadf["barcode"].unique())
plots = []
for barc in barcodes:
logging.info("Processing {}".format(barc))
settings["path"] = path.join(args.outdir,
args.prefix + barc + "_")
dfbarc = datadf[datadf["barcode"] == barc]
if len(dfbarc) > 5:
settings["title"] = barc
plots.extend(make_plots(dfbarc, settings))
else:
sys.stderr.write(
"Found barcode {} less than 5x, ignoring...\n".format(
barc))
logging.info(
"Found barcode {} less than 5 times, ignoring".format(
barc))
else:
plots = make_plots(datadf, settings)
make_report(plots, settings)
logging.info("Finished!")
except Exception as e:
logging.error(e, exc_info=True)
print("\n\n\nIf you read this then NanoPlot {} has crashed :-(".format(
__version__))
print("Please try updating NanoPlot and see if that helps...\n")
print(
"If not, please report this issue at https://github.com/wdecoster/NanoPlot/issues"
)
print(
"If you could include the log file that would be really helpful.")
print("Thanks!\n\n\n")
raise
def main():
'''
Organization function
-setups logging
-gets inputdata
-calls plotting function
'''
args = get_args()
try:
utils.make_output_dir(args.outdir)
logfile = utils.init_logs(args)
args.format = nanoplotter.check_valid_format(args.format)
settings = vars(args)
settings["path"] = path.join(args.outdir, args.prefix)
sources = [
args.fastq, args.bam, args.fastq_rich, args.fastq_minimal,
args.summary
]
sourcename = ["fastq", "bam", "fastq_rich", "fastq_minimal", "summary"]
if args.pickle:
datadf = pickle.load(open(args.pickle, 'rb'))
else:
datadf = get_input(
source=[n for n, s in zip(sourcename, sources) if s][0],
files=[f for f in sources if f][0],
threads=args.threads,
readtype=args.readtype,
combine="simple",
barcoded=args.barcoded)
if args.store:
pickle.dump(obj=datadf,
file=open(settings["path"] + "NanoPlot-data.pickle",
'wb'))
if args.raw:
datadf.to_csv("NanoPlot-data.tsv.gz",
sep="\t",
index=False,
compression="gzip")
statsfile = settings["path"] + "NanoStats.txt"
nanomath.write_stats(datadfs=[datadf], outputfile=statsfile)
logging.info("Calculated statistics")
datadf, settings = filter_data(datadf, settings)
if args.barcoded:
barcodes = list(datadf["barcode"].unique())
statsfile = settings["path"] + "NanoStats_barcoded.txt"
nanomath.write_stats(
datadfs=[datadf[datadf["barcode"] == b] for b in barcodes],
outputfile=statsfile,
names=barcodes)
plots = []
for barc in barcodes:
logging.info("Processing {}".format(barc))
settings["path"] = path.join(args.outdir,
args.prefix + barc + "_")
dfbarc = datadf[datadf["barcode"] == barc]
settings["title"] = barc
plots.extend(make_plots(dfbarc, settings))
settings["path"] = path.join(args.outdir, args.prefix)
else:
plots = make_plots(datadf, settings)
make_report(plots, settings["path"], logfile, statsfile)
logging.info("Finished!")
except Exception as e:
logging.error(e, exc_info=True)
print("\n\n\nIf you read this then NanoPlot has crashed :-(")
print(
"Please report this issue at https://github.com/wdecoster/NanoPlot/issues"
)
print("If you include the log file that would be really helpful.")
print("Thanks!\n\n\n")
raise
def run_tests():
"""Test functions using testdata from the nanotest repo."""
nanoget.get_input("bam", ["nanotest/alignment.bam"])
nanoget.get_input("bam", ["nanotest/alignment.bam"], keep_supp=False)
nanoget.get_input("fastq_rich", ["nanotest/reads.fastq.gz"])
nanoget.get_input("summary", ["nanotest/sequencing_summary.txt"],
combine="track")
nanoget.get_input("fastq_minimal", ["nanotest/reads.fastq.gz"])
nanoget.get_input("fastq", ["nanotest/reads.fastq.gz"])
nanoget.get_input("fasta", ["nanotest/reads.fa.gz"])
def main():
args = getArgs()
fqin = get_input(args.fastqfile.name)
splitFq(fqin, args)
