import click from numpy import unique, ndarray from scipy.sparse.csc import csc_matrix from os.path import isfile, isdir, splitext, expanduser, sep settings = dict(help_option_names=['-h', '--help']) @click.command() @click.argument('dataset', nargs=1, metavar='', required=True) @click.option('--layout', '-l', default=['umap', 'tsne'], multiple=True, type=click.Choice(['umap', 'tsne']), help='layout algorithm', show_default=True) @click.option('--recipe', '-r', default='none', type=click.Choice(['none', 'seurat', 'zheng17']), help='preprocessing to run', show_default=True) @click.option('--output', '-o', default='', help='save a new file to filename', metavar='') @click.option('--set-obs-names', default='', help='named field to set as index for obs', metavar='') @click.option('--set-var-names', default='', help='named field to set as index for var', metavar='') @click.option('--make-obs-names-unique', default=True, is_flag=True, help='ensure obs index is unique', show_default=True) @click.option('--make-var-names-unique', default=True, is_flag=True, help='ensure var index is unique', show_default=True) @click.option('--sparse', default=False, is_flag=True, help='whether to force sparsity', show_default=True) @click.option('--overwriting', default=False, is_flag=True, help='whether to allow file overwriting', show_default=True) @click.option('--plotting', '-p', default=False, is_flag=True, help='whether to generate plots', show_default=True) def cli(dataset, layout, recipe, output, set_obs_names, set_var_names, make_obs_names_unique, make_var_names_unique, sparse, overwriting, plotting): """ preprocesses data for use with cellxgene """ # collect slow imports here to make CLI startup more responsive click.echo('[cellxgene] Starting CLI...') import matplotlib matplotlib.use('Agg') import scanpy.api as sc # scanpy settings sc.settings.verbosity = 0 sc.settings.autosave = True # check args if sparse and not recipe == 'none': raise click.UsageError('Cannot use a recipe when forcing sparsity') output = expanduser(output) if isfile(output) and not overwrite: raise click.UsageError('Cannot overwrite existing file %s, try using the flag --overwrite' % output) def load_data(dataset): if isfile(dataset): name, extension = splitext(dataset) if extension == '.h5ad': adata = sc.read_h5ad(dataset) elif extension == '.loom': adata = sc.read_loom(dataset) else: raise click.FileError(dataset, hint='does not have a valid extension [.h5ad | .loom]') elif isdir(dataset): if not dataset.endswith(sep): dataset += sep adata = sc.read_10x_mtx(dataset) else: raise click.FileError(dataset, hint='not a valid file or path') if not set_obs_names == '': if set_obs_names not in adata.obs_keys(): raise click.UsageError('obs %s not found, options are: %s' % (set_obs_names, adata.obs_keys())) adata.obs_names = adata.obs[set_obs_names] if not set_var_names == '': if set_var_names not in adata.var_keys(): raise click.UsageError('var %s not found, options are: %s' % (set_var_names, adata.var_keys())) adata.var_names = adata.var[set_var_names] if make_obs_names_unique: adata.obs_names_make_unique() if make_var_names_unique: adata.var_names_make_unique() if not adata._obs.index.is_unique: click.echo('Warning: obs index is not unique') if not adata._var.index.is_unique: click.echo('Warning: var index is not unique') return adata def make_sparse(adata): if (type(adata.X) is ndarray) and sparse: adata.X = csc_matrix(adata.X) def run_recipe(adata): if recipe == 'seurat': sc.pp.recipe_seurat(adata) elif recipe == 'zheng17': sc.pp.recipe_zheng17(adata) else: sc.pp.filter_cells(adata, min_genes=5) sc.pp.filter_genes(adata, min_cells=25) if sparse: sc.pp.scale(adata, zero_center=False) else: sc.pp.scale(adata) def run_pca(adata): if sparse: sc.pp.pca(adata, svd_solver='arpack', zero_center=False) else: sc.pp.pca(adata, svd_solver='arpack') def run_neighbors(adata): sc.pp.neighbors(adata) def run_louvain(adata): sc.tl.louvain(adata) def run_layout(adata): if len(unique(adata.obs['louvain'].values)) < 10: palette = 'tab10' else: palette = 'tab20' if layout == 'umap' or layout == 'umap+tsne': sc.tl.umap(adata) if plotting: sc.pl.umap(adata, color='louvain', palette=palette, save='_louvain') if layout == 'tsne' or layout == 'umap+tsne': sc.tl.tsne(adata) if plotting: sc.pl.tsne(adata, color='louvain', palette=palette, save='_louvain') def show_step(item): names = { 'make_sparse': 'Ensuring sparsity', 'run_recipe': 'Running preprocessing recipe "%s"' % recipe, 'run_pca': 'Running PCA', 'run_neighbors': 'Calculating neighbors', 'run_louvain': 'Calculating clusters', 'run_layout': 'Computing layout' } if item is not None: return names[item.__name__] steps = [make_sparse, run_recipe, run_pca, run_neighbors, run_louvain, run_layout] click.echo('[cellxgene] Loading data from %s, please wait...' % dataset) adata = load_data(dataset) click.echo('[cellxgene] Beginning preprocessing...') with click.progressbar(steps, label='[cellxgene] Progress', show_eta=False, item_show_func=show_step) as bar: for step in bar: step(adata) # saving if not output == '': click.echo('[cellxgene] Saving results to %s...' % output) adata.write(output) click.echo('[cellxgene] ' + click.style('Success!', fg='green')) if __name__ == '__main__': cli()