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https://github.com/chanzuckerberg/cellxgene.git
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add CLI tool for dataset preparation using scanpy (#364)
* add prepare cli * fix handling of user path * fixes for linter * add flags and options for handling obs and var names * add prepare cli * fix handling of user path * fixes for linter * add flags and options for handling obs and var names * address review requests
This commit is contained in:
Jeremy Freeman
committed by
Charlotte Weaver
Charlotte Weaver
parent
ed66ae6e4a
commit
75ca14e4aa
159
prepare/cli.py
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159
prepare/cli.py
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import click
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from numpy import unique, ndarray
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from scipy.sparse.csc import csc_matrix
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from os.path import isfile, isdir, splitext, expanduser, sep
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settings = dict(help_option_names=['-h', '--help'])
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@click.command()
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@click.argument('dataset', nargs=1, metavar='<dataset: file or path to data>', required=True)
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@click.option('--layout', '-l', default=['umap', 'tsne'], multiple=True, type=click.Choice(['umap', 'tsne']),
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help='layout algorithm', show_default=True)
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@click.option('--recipe', '-r', default='none', type=click.Choice(['none', 'seurat', 'zheng17']),
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help='preprocessing to run', show_default=True)
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@click.option('--output', '-o', default='', help='save a new file to filename', metavar='<filename>')
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@click.option('--set-obs-names', default='', help='named field to set as index for obs', metavar='<name>')
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@click.option('--set-var-names', default='', help='named field to set as index for var', metavar='<name>')
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@click.option('--make-obs-names-unique', default=True, is_flag=True, help='ensure obs index is unique', show_default=True)
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@click.option('--make-var-names-unique', default=True, is_flag=True, help='ensure var index is unique', show_default=True)
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@click.option('--sparse', default=False, is_flag=True, help='whether to force sparsity', show_default=True)
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@click.option('--overwriting', default=False, is_flag=True, help='whether to allow file overwriting', show_default=True)
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@click.option('--plotting', '-p', default=False, is_flag=True, help='whether to generate plots', show_default=True)
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def cli(dataset, layout, recipe, output, set_obs_names, set_var_names,
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make_obs_names_unique, make_var_names_unique, sparse, overwriting, plotting):
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"""
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preprocesses data for use with cellxgene
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"""
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# collect slow imports here to make CLI startup more responsive
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click.echo('[cellxgene] Starting CLI...')
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import matplotlib
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matplotlib.use('Agg')
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import scanpy.api as sc
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# scanpy settings
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sc.settings.verbosity = 0
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sc.settings.autosave = True
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# check args
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if sparse and not recipe == 'none':
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raise click.UsageError('Cannot use a recipe when forcing sparsity')
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output = expanduser(output)
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if isfile(output) and not overwrite:
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raise click.UsageError('Cannot overwrite existing file %s, try using the flag --overwrite' % output)
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def load_data(dataset):
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if isfile(dataset):
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name, extension = splitext(dataset)
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if extension == '.h5ad':
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adata = sc.read_h5ad(dataset)
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elif extension == '.loom':
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adata = sc.read_loom(dataset)
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else:
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raise click.FileError(dataset, hint='does not have a valid extension [.h5ad | .loom]')
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elif isdir(dataset):
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if not dataset.endswith(sep):
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dataset += sep
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adata = sc.read_10x_mtx(dataset)
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else:
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raise click.FileError(dataset, hint='not a valid file or path')
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if not set_obs_names == '':
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if set_obs_names not in adata.obs_keys():
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raise click.UsageError('obs %s not found, options are: %s' % (set_obs_names, adata.obs_keys()))
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adata.obs_names = adata.obs[set_obs_names]
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if not set_var_names == '':
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if set_var_names not in adata.var_keys():
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raise click.UsageError('var %s not found, options are: %s' % (set_var_names, adata.var_keys()))
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adata.var_names = adata.var[set_var_names]
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if make_obs_names_unique:
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adata.obs_names_make_unique()
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if make_var_names_unique:
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adata.var_names_make_unique()
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if not adata._obs.index.is_unique:
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click.echo('Warning: obs index is not unique')
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if not adata._var.index.is_unique:
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click.echo('Warning: var index is not unique')
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return adata
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def make_sparse(adata):
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if (type(adata.X) is ndarray) and sparse:
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adata.X = csc_matrix(adata.X)
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def run_recipe(adata):
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if recipe == 'seurat':
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sc.pp.recipe_seurat(adata)
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elif recipe == 'zheng17':
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sc.pp.recipe_zheng17(adata)
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else:
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sc.pp.filter_cells(adata, min_genes=5)
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sc.pp.filter_genes(adata, min_cells=25)
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if sparse:
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sc.pp.scale(adata, zero_center=False)
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else:
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sc.pp.scale(adata)
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def run_pca(adata):
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if sparse:
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sc.pp.pca(adata, svd_solver='arpack', zero_center=False)
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else:
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sc.pp.pca(adata, svd_solver='arpack')
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def run_neighbors(adata):
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sc.pp.neighbors(adata)
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def run_louvain(adata):
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sc.tl.louvain(adata)
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def run_layout(adata):
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if len(unique(adata.obs['louvain'].values)) < 10:
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palette = 'tab10'
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else:
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palette = 'tab20'
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if layout == 'umap' or layout == 'umap+tsne':
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sc.tl.umap(adata)
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if plotting:
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sc.pl.umap(adata, color='louvain', palette=palette, save='_louvain')
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if layout == 'tsne' or layout == 'umap+tsne':
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sc.tl.tsne(adata)
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if plotting:
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sc.pl.tsne(adata, color='louvain', palette=palette, save='_louvain')
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def show_step(item):
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names = {
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'make_sparse': 'Ensuring sparsity',
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'run_recipe': 'Running preprocessing recipe "%s"' % recipe,
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'run_pca': 'Running PCA',
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'run_neighbors': 'Calculating neighbors',
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'run_louvain': 'Calculating clusters',
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'run_layout': 'Computing layout'
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}
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if item is not None:
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return names[item.__name__]
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steps = [make_sparse, run_recipe, run_pca, run_neighbors, run_louvain, run_layout]
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click.echo('[cellxgene] Loading data from %s, please wait...' % dataset)
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adata = load_data(dataset)
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click.echo('[cellxgene] Beginning preprocessing...')
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with click.progressbar(steps, label='[cellxgene] Progress', show_eta=False, item_show_func=show_step) as bar:
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for step in bar:
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step(adata)
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# saving
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if not output == '':
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click.echo('[cellxgene] Saving results to %s...' % output)
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adata.write(output)
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click.echo('[cellxgene] ' + click.style('Success!', fg='green'))
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if __name__ == '__main__':
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cli()
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@@ -1,4 +1,5 @@
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anndata==0.6.11
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click==6.7
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Flask==0.12.4
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Flask-Caching==1.4.0
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Flask-Compress==1.4.0
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@@ -9,4 +10,4 @@ numpy==1.14.5
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pandas==0.23.1
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scanpy==1.3.2
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scipy==1.1.0
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scikit-learn==0.19.1
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scikit-learn==0.19.1
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