Step11_figures.figure5b_volcanoPlot_retromer_mfComparison(folder = main_figure5b_boxPlots(**kwargs): Print('volcano_plot_stoichiometry:retromer complex') Step11_figures.figure5b_volcanoPlot_cohesin_mfComparison(folder = output_folder) Print('volcano_plot_stoichiometry:Cohesin') Step11_figures.figure5b_volcanoPlot_cop2_mfComparison(folder = output_folder) Print('volcano_plot_stoichiometry:COPII') Step11_figures.figure5b_volcanoPlot_cop1_mfComparison(folder = output_folder) 'complex_label': main_figure5b_volcanoPlots(**kwargs): Pval_list = -np.log10(np.array(data))Ĭomplex_pval_list = -np.log10(np.array(complex_data))Ĭomplex_fc_list = np.array(complex_data)Ĭomplex_label_list = list(complex_data.index)Ĭomplex_colors = )] Plt.savefig(folder + 'fig5a_abundance_diet_stoichiometry_comparison.pdf',ībox_inches = 'tight', dpi = get_data(name,**kwargs):įilename = 'gygi3_complex_mf_'ĭata = DataFrameAnalyzer.open_in_chunks(folder, filename)ĭata = dataĭata = data.drop(, axis = 0)Ĭomplex_data = data Plt.xticks(list(ange(0.5,len(complex_list) + 0.5,1)))Īx.set_xticklabels(complex_list,rotation = 90, fontsize = 7) Rects2 = ax.bar(ind, variable_fractions, width, color='red',bottom = np.array(stable_fractions), Rects1 = ax.bar(ind, stable_fractions, width, color='darkblue', edgecolor = 'white') Rects = ax.bar(ind, cohen_list, width, color=colors,Īx.set_xlim(-0.1, len(complex_list) + 0.1) Tt_pvalCorrs = rrect_pvalues(tt_pval_list) Tt_pval_list.append(abu_data.loc)Ĭomplex_list.append(':'.join(key.split(':')))Ĭohen_list,complex_list,tt_pval_list,stable_fractions, variable_fractions = utilsFacade.sort_multiple_lists(, reverse = True) Gold = complexDictĬohen_list.append(abu_data.loc) Key_list = list(set(abu_data.index).intersection(set(cov_sig_dict.keys()))) 'figure5a_gygi3_complex_diet_total_abundance_') Return get_complex_abundance_data(cov_sig_dict, num_dict, **kwargs):ĬomplexDict = step11_preparation.get_complex_dictionary(folder = folder)Ību_data = DataFrameAnalyzer.open_in_chunks(folder, Return get_complex_dictionary(**kwargs):ĬomplexDict = DataFrameAnalyzer.read_pickle(folder + 'complex_dictionary.pkl') Return cov_sig_dict, get_stoichiometric_hits_per_complex_dict(**kwargs):Ĭov_sig_dict = DataFrameAnalyzer.read_pickle(folder + 'figure5a_stoichiometric_hits_per_complex_dict.pkl') #DataFrameAnalyzer.to_pickle(num_dict, folder + 'figure5a_stoichiometric_diet_hitsNUM_per_complex_dict.pkl')

#DataFrameAnalyzer.to_pickle(cov_sig_dict, folder + 'figure5a_stoichiometric_diet_hits_per_complex_dict.pkl') #run similarly for diet differences as well Stoch_sig_sub = stoch_sub 0.01]Ĭoverage = float(len(stoch_sig_sub))/float(len(stoch_sub))*100ĭataFrameAnalyzer.to_pickle(cov_sig_dict, folder + 'figure5a_stoichiometric_hits_per_complex_dict.pkl')ĭataFrameAnalyzer.to_pickle(num_dict, folder + 'figure5a_stoichiometric_hitsNUM_per_complex_dict.pkl') Return data, quant_data, prepare_stochiometry_hit_dictionary(**kwargs):ĭata = step11_preparation.get_limma_data(folder = folder)Ĭomplex_set = list(set(plex_search)) #same for diet for Supplementary informationĭata = DataFrameAnalyzer.open_in_chunks(folder, 'gygi3_complex_hs_', Step11_preparation.prepare_data_for_second_graph(folder = get_limma_data(**kwargs):ĭata = DataFrameAnalyzer.open_in_chunks(folder, 'gygi3_complex_mf_', Output_folder = kwargs.get('output_folder','PATH')

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