def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
sep = get_seperator(args.sep)
experiments = models.load_experiments(args.experiments, sep=sep)
libraries = models.load_library_tables(args.libraries, sep=sep)
output_sep = get_seperator(args.output_format)
output_extension = {"TAB": ".tsv", ",": ".csv"}[args.output_format]
if args.transcriptome:
# isoforms
load_quantifications = madqc.load_transcriptome_quantifications
quantification_extension = "_isoform_" + args.quantification + output_extension
else:
# genes
load_quantifications = madqc.load_genomic_quantifications
quantification_extension = "_gene_" + args.quantification + output_extension
for name in experiments:
filename = name + quantification_extension
replicates = experiments[name]
logger.info("%s %s: %s", name, args.quantification, ",".join(replicates))
quantifications = load_quantifications(replicates, libraries, args.quantification)
quantifications.to_csv(filename, sep=output_sep)
def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
sep = get_seperator(args.sep)
experiments = models.load_experiments(args.experiments, sep=sep)
libraries = models.load_library_tables(args.libraries, sep=sep)
output_sep = get_seperator(args.output_format)
output_extension = {
'TAB': '.tsv',
',': '.csv',
}[args.output_format]
if args.add_names:
if args.gtf_cache is None:
parser.error('GTF-cache is needed to add names to the quantification file')
else:
logger.info('Loading GTF Cache %s', args.gtf_cache)
annotation = models.load_gtf_cache(args.gtf_cache)
else:
annotation = None
if args.transcriptome:
# isoforms
load_quantifications = madqc.load_transcriptome_quantifications
lookup_ids = models.lookup_gene_name_by_transcript_id
quantification_extension = '_isoform_' + args.quantification + output_extension
else:
# genes
load_quantifications = madqc.load_genomic_quantifications
lookup_ids = models.lookup_gene_name_by_gene_id
quantification_extension = '_gene_' + args.quantification + output_extension
for name in experiments:
filename = name + quantification_extension
replicates = experiments[name]
logger.info("%s %s: %s",
name, args.quantification, ','.join(replicates))
quantifications = load_quantifications(
replicates, libraries, args.quantification)
if annotation is not None:
quantifications = lookup_ids(annotation, quantifications)
quantifications.to_csv(filename, sep=output_sep)
def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
if not validate_path_args(args):
parser.error('Please set required parameters')
if not (validate_library_file_existance(args) and
validate_experiment_file_existance(args)):
parser.error('Fix path to files')
sep = get_seperator(args.sep)
library_filenames = args.libraries
library_filenames.extend(args.other_libraries)
libraries = models.load_library_tables(library_filenames, sep)
read1 = dict(find_fastqs(libraries, 'read_1'))
if 'read_2' in libraries.columns:
read2 = dict(find_fastqs(libraries, 'read_2'))
else:
read2 = {}
dags = generate_star_rsem_analysis(args, libraries, read1, read2)
generate_combined_analysis(args, dags)
return 0
def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
sep = get_seperator(args.sep)
if not validate_library_file_existance(args):
parser.error('Fix incorrect library file names')
library_filenames = args.libraries
if len(library_filenames) == 0:
parser.error('Need library information table')
libraries = load_library_tables(library_filenames, sep)
custom_tracks = []
for library_id, library in libraries.iterrows():
if args.bigwig:
custom_tracks.extend(
make_bigwig_custom_tracks(library, args.web_root, args.root))
if args.bam:
custom_tracks.append(
make_bam_custom_track(library, args.web_root, args.root))
print(os.linesep.join(custom_tracks))
def save(self, quantifications, output_format, filename=None):
output_sep = get_seperator(output_format)
output_extension = {
'TAB': '.reads_per_gene.tsv',
',': '.reads_per_gene.csv',
}[output_format]
if filename is None:
filename = quantifications.name + output_extension
quantifications.to_csv(filename, sep=output_sep)
def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
sep = get_seperator(args.sep)
experiments = models.load_experiments(args.experiments, sep=sep)
libraries = models.load_library_tables(args.libraries, sep=sep)
if args.add_names:
if args.gtf_cache is None:
parser.error('GTF-cache is needed to add names to the quantification file')
else:
logger.info('Loading GTF Cache %s', args.gtf_cache)
annotation = models.load_gtf_cache(args.gtf_cache)
else:
annotation = None
loader = StarLoader(args.strand, annotation)
for i, experiment in experiments.iterrows():
quantification = loader.load(experiment, libraries)
loader.save(quantification, args.output_format)
def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
sep = get_seperator(args.sep)
experiments = models.load_experiments(args.experiments, sep=sep)
libraries = models.load_library_tables(args.libraries, sep=sep)
gtf_cache = None
if args.add_names:
if args.genome_dir is None:
parser.error(
'genome-dir is needed to add names to the quantification file')
else:
gtf_cache = GTFCache(libraries, args.genome_dir)
if len(args.quantification) > 0:
quantification_list = args.quantification
else:
quantification_list = ['FPKM']
if args.transcriptome:
# isoforms
RsemLoader = IsoformRsemLoader
else:
# genes
RsemLoader = GeneRsemLoader
for quantification in quantification_list:
logger.info('Building expression matrix for %s', quantification)
for i, experiment in experiments.iterrows():
loader = RsemLoader(quantification, gtf_cache)
matrix = loader.load(experiment, libraries)
loader.save(matrix, args.output_format)
def main(cmdline=None):
parser = make_parser()
args = parser.parse_args(cmdline)
configure_logging(args)
if args.version:
parser.exit(0, 'version: %s\n' % (get_git_version(),))
if not validate_args(args):
parser.error("Please set required parameters")
sep = get_seperator(args.sep)
libraries = models.load_library_tables(args.libraries, sep)
read1 = dict(find_fastqs(libraries, 'read_1'))
if 'read_2' in libraries.columns:
read2 = dict(find_fastqs(libraries, 'read_2'))
else:
read2 = {}
dag = generate_star_rsem_analysis(args, libraries, read1, read2)
print(dag)
return 0
def test_get_seperator(self):
self.assertEqual(get_seperator('tab'), '\t')
self.assertEqual(get_seperator('TaB'), '\t')
self.assertEqual(get_seperator(','), ',')
self.assertRaises(ValueError, get_seperator, '|')