stereo.algorithm.batch_qc.BatchQc.main#

BatchQc.main(n_neighbors=100, condition=None, count_key='total_counts', cluster_res_key=None, report_path='./batch_qc', gpu='0', data_loader_num_workers=10, num_threads=-1, res_key='batch_qc')[source]#

_summary_

Parameters:

  • n_neighbors (int) – Calculate the nearest neighbors of a local area, defaults to 100.

  • condition (Union[str, list, None]) – Label the experimental conditions. By default, the experimental conditions for each data are different, defaults to None.

  • count_key (str) – total_counts or n_genes_by_counts, defaults to “total_counts”.

  • cluster_res_key (Optional[str]) – The key which specifies the clustering result in data.tl.result, defaults to None.

  • report_path (str) – The path to save the reports of result, defaults to “./batch_qc”.

  • gpu (Union[str, int]) – The gpu on which running this function, defaults to “0”, it will run on cpu automatically if the machine doesn’t have gpu.

  • res_key (str) – Set a key to store the result to data.tl.result, defaults to ‘batch_qc’.

  • data_loader_num_workers (int) – ‘int’, will create data_loader_num_workers num of multiprocessing to work.

  • num_threads (int) – ‘int’, will create num_threads num of threads to work.