('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,