davae.utils package

Submodules

davae.utils.plot module

davae.utils.tools module

davae.utils.tools.cacu_Manhattan_dist(dataset)[source]
davae.utils.tools.cacu_clustering_metrics(x_list, label, metrics_list)[source]
davae.utils.tools.cacu_color(X, i)[source]
davae.utils.tools.cacu_size_factor(adata)[source]
davae.utils.tools.filt(adata, min_c, min_g)[source]
davae.utils.tools.filt_genes(x, min_cells=0)[source]
davae.utils.tools.find_gene_pos(genes, gene)[source]
davae.utils.tools.get_ifnb(tech='stim', type='')[source]
davae.utils.tools.get_intersection_panc8(tech, norm=True)[source]
davae.utils.tools.get_label_by_count(label_path)[source]
davae.utils.tools.get_label_by_txt(txtpath)[source]
davae.utils.tools.get_panc8(tech, type='')[source]
davae.utils.tools.intersection_genes(data1, data2, genes1, genes2)[source]
davae.utils.tools.joint_cluster_feature(dataset, k)[source]
davae.utils.tools.locate_sample(barcodes, barcode)[source]
davae.utils.tools.merge(files, type='h5ad')[source]
davae.utils.tools.multi_intersection_genes(data_list, gene_list)[source]
davae.utils.tools.multi_up_sampling(x, batch_size)[source]
davae.utils.tools.read_sc_data(input_file, fmt='h5ad', backed=None, transpose=False, sparse=False, delimiter=' ')[source]
davae.utils.tools.sample_by_reference(ref_barcodes, barcodes, data)[source]
davae.utils.tools.seurat_preprocession(adata, min_cells, min_genes)[source]
davae.utils.tools.text_label_to_number(txt_label)[source]
davae.utils.tools.txt_to_adata(txt_path)[source]
davae.utils.tools.up_sampling(x, y, batch_size)[source]
davae.utils.tools.write_count(count, out_path)[source]
davae.utils.tools.write_merge_label(count, labels, path)[source]

Module contents