('HTR1A', 'MFC'),
]
n_bins = 50
n_samples = 10
disable_all_warnings()
cfg.verbosity = 1
age_scaler = LogScaler()
data = GeneData.load('both').restrict_pathway(pathway).scale_ages(age_scaler)
shape = Sigmoid(priors='sigmoid_wide')
fitter = Fitter(shape, sigma_prior='normal')
fits = get_all_fits(data, fitter, allow_new_computation=False)
dirname = 'bootstrap'
fits = add_change_distributions(data, fitter, fits, n_bins=n_bins)
fig = plot_bootstrap_onset_variance(data, fits)
save_figure(fig,
'{}/onset-variance-{}.png'.format(dirname, pathway),
under_results=True,
b_close=True)
fig = plot_change_width_scatter(data, fitter, fits)
save_figure(fig,
'{}/width-scatter-{}.png'.format(dirname, pathway),
under_results=True,
b_close=True)
for g, r in gene_regions:
ds_name = data.region_to_dataset()[r]
if args.onset and not is_sigmoid:
abort('--onset can only be used with sigmoid fits')
if args.change_dist and not is_sigmoid:
abort('--change_dist can only be used with sigmoid fits')
if args.onset and args.html == NOT_USED:
abort('--onset should only be used with --html')
if args.text and args.shape != 'spline':
abort('--text only supported for splines at the moment')
k_of_n = parse_k_of_n(args.part)
correlations_k_of_n = parse_k_of_n(args.correlations_part)
data, fitter = process_common_inputs(args)
fits = do_fits(data, fitter, k_of_n, args.correlations, correlations_k_of_n)
has_change_distributions = is_sigmoid
if has_change_distributions:
print 'Computing change distributions...'
add_change_distributions(data, fitter, fits)
if args.change_dist:
print 'Computing region pair timing measures...'
compute_dprime_measures_for_all_pairs(data, fitter, fits)
export_timing_info_for_all_fits(data, fitter, fits)
if args.html != NOT_USED:
if args.correlations:
correlations = {r: rfits[-1].correlations for r,rfits in iterate_region_fits(data, fits)}
else:
correlations = None
create_html(data, fitter, fits, args.html, k_of_n,
use_correlations=args.correlations,
correlations=correlations,
show_onsets=args.onset,
show_change_distributions = has_change_distributions and not args.dont_show_change_dist,
no_legend = args.no_legend,
('HTR1A', 'MFC'),
]
n_bins = 50
n_samples = 10
disable_all_warnings()
cfg.verbosity = 1
age_scaler = LogScaler()
data = GeneData.load('both').restrict_pathway(pathway).scale_ages(age_scaler)
shape = Sigmoid(priors='sigmoid_wide')
fitter = Fitter(shape, sigma_prior='normal')
fits = get_all_fits(data, fitter, allow_new_computation=False)
dirname = 'bootstrap'
fits = add_change_distributions(data, fitter, fits, n_bins=n_bins)
fig = plot_bootstrap_onset_variance(data, fits)
save_figure(fig, '{}/onset-variance-{}.png'.format(dirname, pathway), under_results=True, b_close=True)
fig = plot_change_width_scatter(data, fitter, fits)
save_figure(fig, '{}/width-scatter-{}.png'.format(dirname, pathway), under_results=True, b_close=True)
for g,r in gene_regions:
ds_name = data.region_to_dataset()[r]
fit = fits[ds_name][(g,r)]
fig = plot_bootstrap_fits(data, fit, n_bins=n_bins, n_samples=n_samples)
save_figure(fig, '{}/fits-{}-{}.png'.format(dirname,g,r), under_results=True, b_close=True)
fig = plot_bootstrap_histograms(data, fit, n_bins=n_bins, n_samples=n_samples)
save_figure(fig, '{}/transition-distribution-{}-{}.png'.format(dirname,g,r), under_results=True, b_close=True)
if args.onset and args.html == NOT_USED:
abort('--onset should only be used with --html')
if args.text and args.shape != 'spline':
abort('--text only supported for splines at the moment')
if (args.exons_layout or args.exons_same_scale or args.exons_plots_from_series) and args.html == NOT_USED:
abort('exons settings are relevant only when using --html')
if (args.exons_same_scale or args.plots_scaling is not 'none') and args.exons_plots_from_series:
abort('--exons_same_scale/--plots_scaling are relevant only when not using --exons_plots_from_series')
k_of_n = parse_k_of_n(args.part)
correlations_k_of_n = parse_k_of_n(args.correlations_part)
data, fitter = process_common_inputs(args)
fits = do_fits(data, fitter, k_of_n, args.correlations, correlations_k_of_n)
has_change_distributions = is_sigmoid
if has_change_distributions:
print 'Computing change distributions...'
add_change_distributions(data, fitter, fits)
if args.change_dist:
print 'Computing region pair timing measures...'
compute_dprime_measures_for_all_pairs(data, fitter, fits)
export_timing_info_for_all_fits(data, fitter, fits)
if args.html != NOT_USED:
if args.correlations:
correlations = {r: rfits[-1].correlations for r,rfits in iterate_region_fits(data, fits)}
else:
correlations = None
exons_layout = args.exons_layout and cfg.exon_level
cfg.exons_same_scale = args.exons_same_scale
cfg.plots_scaling = args.plots_scaling
cfg.exons_plots_from_series = args.exons_plots_from_series
create_html(data, fitter, fits, args.html, k_of_n,
use_correlations=args.correlations,
