def main(args=None):
"""The main routine."""
if args is None:
args = sys.argv[1:]
commands = [
('Main Comand (Must be run before any other commands):',
[('genome_resquiggle', 'Re-annotate raw signal with ' +
'genomic aignement of existing basecalls.',
option_parsers.get_resquiggle_parser(), resquiggle.resquiggle_main)
]),
('Genome Anchored Plotting Commands:',
[('plot_max_coverage',
'Plot signal in regions with the maximum coverage.',
option_parsers.get_max_cov_parser(), plot_commands.max_cov_main),
('plot_genome_location', 'Plot signal at defined genomic locations.',
option_parsers.get_genome_loc_parser(),
plot_commands.genome_loc_main),
('plot_motif_centered',
'Plot signal at regions centered on a specific motif.',
option_parsers.get_motif_loc_parser(),
plot_commands.motif_loc_main),
('plot_max_difference',
'Plot signal where signal differs the most ' +
'between two groups.', option_parsers.get_max_diff_parser(),
plot_commands.max_diff_main),
('plot_most_significant',
'Plot signal where signal differs the most ' +
'significantly between two groups.',
option_parsers.get_signif_diff_parser(),
plot_commands.signif_diff_main),
('plot_motif_with_stats',
'Plot signal from several regions and test ' +
'statistics centered on a k-mer of interst.',
option_parsers.get_signif_motif_parser(),
plot_commands.motif_signif_diff_main)]),
('Sequencing Time Anchored Plotting Command:',
[('plot_correction', 'Plot segmentation before and after correction.',
option_parsers.get_correction_parser(),
plot_commands.plot_correction_main),
('plot_multi_correction',
'Plot multiple raw signals anchored by genomic location.',
option_parsers.get_multi_correction_parser(),
plot_commands.plot_multi_correction_main)]),
('Other Plotting Commands:',
[('cluster_most_significant',
'Clustering traces at bases with significant differences.',
option_parsers.get_cluster_signif_diff_parser(),
plot_commands.cluster_signif_diff_main),
('plot_kmer', 'Plot signal quantiles acorss kmers.',
option_parsers.get_kmer_dist_parser(), plot_commands.kmer_dist_main)
]),
('Auxiliary Commands:',
[('write_most_significant_fasta',
'Write sequence where signal differs the most ' +
'significantly between two groups.',
option_parsers.get_write_signif_diff_parser(),
text_output_commands.write_signif_diff_main),
('write_wiggles', 'Write wiggle files for nanopore ' +
'signal values, coverage, and statistics.',
option_parsers.get_wiggle_parser(),
text_output_commands.wiggle_main)]),
]
desc = '\n\n'.join([
grp + '\n' + '\n'.join([
'\t{0: <30}{1}'.format(cmd, cmd_help)
for cmd, cmd_help, cmd_parser, cmd_main in cmds
]) for grp, cmds in commands
])
import argparse
parser = argparse.ArgumentParser(
prog='nanoraw',
description='nanoraw is a command line and python toolset ' +
'to analyze and visualize raw nanopore sequencing data.',
formatter_class=argparse.RawDescriptionHelpFormatter)
subparsers = parser.add_subparsers(
title='commands',
description=desc,
help='Additional help available for subcommands.')
# fill subparser with parsers and linked main functions
for grp, cmds in commands:
for cmd, cmd_help, cmd_parser, cmd_main in cmds:
subparser_cmd = subparsers.add_parser(cmd,
parents=[
cmd_parser,
],
add_help=False)
subparser_cmd.set_defaults(func=cmd_main)
args = parser.parse_args(args)
args.func(args)
return
def main(args=None):
"""The main routine."""
if args is None:
args = sys.argv[1:]
commands = [
('Resquiggle (Must be run before any other commands):', [
('resquiggle', 'Re-annotate raw signal with ' +
'genomic alignment from existing basecalls.',
option_parsers.get_eventless_resquiggle_parser()),
]),
('Statistical Testing Command:', [
('test_significance', 'Test for shifts in signal ' +
'indicative of non-canonical bases.',
option_parsers.get_test_signif_parser()),
]),
('Text Output Commands:', [
('write_wiggles', 'Write text outputs for genome browser ' +
'visualization and bioinformatic processing (wiggle file format).',
option_parsers.get_wiggle_parser()),
('write_most_significant_fasta',
'Write sequence centered on most modified genomic locations.',
option_parsers.get_write_signif_diff_parser()),
]),
('Genome Anchored Plotting Commands:', [
('plot_max_coverage',
'Plot raw signal in regions with maximal coverage.',
option_parsers.get_max_cov_parser()),
('plot_genome_location',
'Plot raw signal at defined genomic locations.',
option_parsers.get_genome_loc_parser()),
('plot_motif_centered', 'Plot raw signal at a specific motif.',
option_parsers.get_motif_loc_parser()),
('plot_max_difference',
'Plot raw signal where signal differs most between two read groups.',
option_parsers.get_max_diff_parser()),
('plot_most_significant',
'Plot raw signal at most modified locations.',
option_parsers.get_signif_diff_parser()),
('plot_motif_with_stats',
'Plot example signal and statistic distributions around a ' +
'motif of interst.', option_parsers.get_signif_motif_parser()),
('plot_per_read', 'Plot per read modified base probabilities.',
option_parsers.get_per_read_parser()),
]),
('Other Plotting Commands:', [
('plot_kmer', 'Plot signal distributions acorss kmers.',
option_parsers.get_kmer_dist_parser()),
('cluster_most_significant',
'Clustering traces at bases with most significant stats.',
option_parsers.get_cluster_signif_diff_parser()),
]),
('Read Filtering (Only effects tombo index file):', [
('clear_filters',
'Clear filters to process all successfully re-squiggled reads.',
option_parsers.get_clear_filters_parser()),
('filter_stuck',
'Apply filter based on observations per base thresholds.',
option_parsers.get_filter_stuck_parser()),
('filter_coverage',
'Apply filter to downsample for more even coverage.',
option_parsers.get_filter_coverage_parser()),
]),
('Event-based Re-squiggle and Model Estimation:', [
('estimate_reference',
'Estimate reference tombo model derived from the provided reads.',
option_parsers.get_est_ref_parser()),
('estimate_alt_reference',
'Estimate alternative tombo model from ' +
'a sample containing canonical bases spiked with a single ' +
'non-standard base.', option_parsers.get_est_alt_ref_parser()),
('estimate_scale', 'Estimate a global scaling parameter from a ' +
'sub-set of reads.', option_parsers.get_estimate_scale_parser()),
('event_resquiggle', 'Re-annotate raw signal with genomic ' +
'alignment from existing basecalls using event table.',
option_parsers.get_event_resquiggle_parser()),
('model_resquiggle', 'Re-annotate raw signal after ' +
'event_resquiggle to more closely match a tombo model.',
option_parsers.get_model_resquiggle_parser()),
]),
('Sequencing Time Anchored Plotting Commands (event_resquiggle only):',
[
('plot_correction',
'Plot segmentation before and after correction.',
option_parsers.get_correction_parser()),
('plot_multi_correction',
'Plot multiple raw signals anchored by genomic location.',
option_parsers.get_multi_correction_parser()),
]),
]
desc = '\n\n'.join([
grp + '\n' + '\n'.join([
'\t{0: <30}{1}'.format(cmd, cmd_help)
for cmd, cmd_help, cmd_parser in cmds
]) for grp, cmds in commands
])
import argparse
parser = argparse.ArgumentParser(
prog='tombo',
description='Tombo is a command line python toolset ' +
'to analyze and visualize raw nanopore sequencing data ' +
'including the identification of non-standard nucleotides.',
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('-v',
'--version',
action='version',
version='tombo version: {}'.format(TOMBO_VERSION),
help='show tombo version and exit.')
subparsers = parser.add_subparsers(
title='commands',
description=desc,
help='Additional help available for subcommands.')
# fill subparser with parsers and linked main functions
for grp, cmds in commands:
for cmd, cmd_help, cmd_parser in cmds:
subparser_cmd = subparsers.add_parser(cmd,
parents=[
cmd_parser,
],
add_help=False)
subparser_cmd.set_defaults(subcmd=cmd, group=grp)
args = parser.parse_args(args)
if args.subcmd == 'resquiggle':
import resquiggle
resquiggle.eventless_resquiggle_main(args)
elif args.subcmd == 'event_resquiggle':
import event_resquiggle
event_resquiggle.event_resquiggle_main(args)
elif args.subcmd == 'model_resquiggle':
import model_resquiggle
model_resquiggle.model_resquiggle_main(args)
elif args.subcmd == 'test_significance':
import tombo_stats
tombo_stats.test_shifts_main(args)
elif args.subcmd == 'estimate_reference':
import tombo_stats
tombo_stats.est_ref_main(args)
elif args.subcmd == 'estimate_alt_reference':
import tombo_stats
tombo_stats.est_alt_ref_main(args)
elif args.subcmd == 'estimate_scale':
import tombo_stats
tombo_stats.estimate_scale_main(args)
elif args.subcmd == 'clear_filters':
import tombo_helper
tombo_helper.clear_filters_main(args)
elif args.subcmd == 'filter_stuck':
import tombo_helper
tombo_helper.filter_stuck_main(args)
elif args.subcmd == 'filter_coverage':
import tombo_helper
tombo_helper.filter_coverage_main(args)
elif args.group == 'Text Output Commands:':
import text_output_commands
if args.subcmd == 'write_wiggles':
text_output_commands.wiggle_main(args)
else:
text_output_commands.write_signif_diff_main(args)
else:
import plot_commands
plot_commands.plot_main(args)
return