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dataset = load_dataset(source='upload') results['pca'] = analyze(dataset=dataset, tool='pca', nr_genes=2500, normalization='logCPM', z_score=True, plot_type='interactive') results['clustergrammer'] = analyze(dataset=dataset, tool='clustergrammer', nr_genes=2500, normalization='logCPM', z_score=True)
script_dirs = [os.path.join(os.path.dirname(os.path.realpath(__file__)), x) for x in ['core_scripts/*', 'analysis_tools/*']] for script_dir in script_dirs: for script_path in glob.glob(script_dir): sys.path.append(script_path) exec('import '+os.path.basename(script_path)) exec('import signature as sig')
# Analyze def analyze(tool, **kwargs): # Normalize, if specified normalization_method = kwargs.get('normalization') if normalization_method and normalization_method not in kwargs['dataset'].keys(): kwargs['dataset'][normalization_method] = normalize_dataset(method = normalization_method, dataset=kwargs['dataset']) return {'results': eval(tool).run(**kwargs), 'tool': tool} # Plot def plot(results, **kwargs): return eval(results['tool']).plot(results['results'], plot_counter=plot_counter, **kwargs)