scprep
Project description
Tools for loading and preprocessing biological matrices in Python.
Installation
preprocessing is available on pip. Install by running the following in a terminal:
pip install --user scprep
Usage example
You can use scprep with your single cell data as follows:
import scprep # Load data data_path = "~/mydata/my_10X_data" data = scprep.io.load_10X(data_path) # Remove empty columns and rows data = scprep.filter.remove_empty_cells(data) data = scprep.filter.remove_empty_genes(data) # Filter by library size to remove background scprep.plot.plot_library_size(data, cutoff=500) data = scprep.filter.filter_library_size(data, cutoff=500) # Filter by mitochondrial expression to remove dead cells mt_genes = scprep.utils.get_gene_set(data, starts_with="MT") scprep.plot.plot_gene_set_expression(data, mt_genes, percentile=90) data = scprep.filter.filter_gene_set_expression(data, mt_genes, percentile=90) # Library size normalize data = scprep.normalize.library_size_normalize(data) # Square root transform data = scprep.transform.sqrt(data)
Help
If you have any questions or require assistance using scprep, please read the documentation at https://scprep.readthedocs.io/ or contact us at https://krishnaswamylab.org/get-help
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