Metadata-Version: 2.3
Name: pybayesprism
Version: 0.0.3
Summary: Python implementation of BayesPrism
Project-URL: Homepage, https://github.com/ziluwang829/pyBayesPrism
Project-URL: Issues, https://github.com/ziluwang829/pyBayesPrism/issues
Author-email: Zilu Wang <zw427@cornell.edu>
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: tqdm
Requires-Dist: xarray
Description-Content-Type: text/markdown

This is a Python implementation of [BayesPrism](https://github.com/Danko-Lab/BayesPrism).


Usage
```
import pybayesprism import *

sc_dat_filtered = process_input.cleanup_genes(sc_dat, "count.matrix", "hs", \
                  ["Rb", "Mrp", "other_Rb", "chrM", "MALAT1", "chrX", "chrY"], 5)
                  
sc_dat_filtered_pc = process_input.select_gene_type(sc_dat_filtered, ["protein_coding"])

my_prism = prism.Prism.new(reference = sc_dat_filtered_pc, 
                          mixture = bk_dat, input_type = "count.matrix", 
                          cell_type_labels = cell_type_labels, 
                          cell_state_labels = cell_state_labels, 
                          key = "tumor", 
                          outlier_cut = 0.01, 
                          outlier_fraction = 0.1)

bp_res = my_prism.run(n_cores = 36, update_gibbs = True)      
```
