ST data deconvolution and spot annotation

If using an external R installation (may not be necessary on Linux systems).

import os
os.environ['R_HOME'] = 'C:/Program Files/R/R-4.4.1'

import the packages

import os
import sys
import cytobulk as ct
import scanpy as sc
import pandas as pd
import warnings
warnings.filterwarnings("ignore")

Load scRNA-seq and ST data

Load the mouse mob reference single cell data, e.g. GSE121891 [Download data]. and ST data from Stahl, Patrik L., et al.[Download data].

sc_adata = sc.read_h5ad(r"C:/Users/wangxueying/project/CytoBulk/case/mouse_mob/mouse_mob_input/sc_layer_mob.h5ad")
st_adata = sc.read_h5ad(r"C:/Users/wangxueying/project/CytoBulk/case/mouse_mob/mouse_mob_input/st_mob.h5ad")

Deconvolute ST data with sc-RNA seq as the reference.

If you want to use the pretrained model, please download the folder, extract it, and set the path of the extracted folder as the out_dir parameter. [Download] This will help you skip the training steps.

deconv_result,deconv_adata = ct.tl.st_deconv(st_adata = st_adata,
                                             sc_adata = sc_adata,
                                             annotation_key ="subtype",
                                             out_dir="C:/Users/wangxueying/project/CytoBulk/case/MOB_layer",
                                             dataset_name="MOB_layer",
                                             different_source=True,
                                             n_cell=15)

deconv_result.head(5)

	EPL	GC	MTC	OSN	PGC
GTCCGATATGATTGCCGC	0.221902	0.624702	0.107771	0.045624	0.000000
ATGAGCCGGGTTCATCTT	0.075856	0.668691	0.090633	0.061275	0.103544
TGAGGCACTCTGTTGGGA	0.042809	0.042166	0.262430	0.212727	0.439867
ATGATTAGTCGCCATTCG	0.039683	0.074653	0.581873	0.104038	0.199753
ACTTGAGGGTAGATGTTT	0.067761	0.106935	0.166045	0.487240	0.172019

Visualization of spot annotation results

ct.plots.celltype_fraction_pie(adata=deconv_adata,
                                scale_facter_x=5,
                                scale_factor_y=5,
                                out_dir="C:/Users/wangxueying/project/CytoBulk/case/MOB_layer",
                                rotation_angle=225)

ct.plots.celltype_fraction_heatmap(adata=deconv_adata,
                                    label='OSN',
                                    out_dir="C:/Users/wangxueying/project/CytoBulk/case/MOB_layer",
                                    rotation_angle=225)

ct.plots.paired_violin(adata=deconv_adata,
                        label='OSN',
                        gene='Kctd12',
                        out_dir="C:/Users/wangxueying/project/CytoBulk/case/mouse_mob_1/output/output")