Import Thor as:

import thor

API

fineST class for prediction of cellular level gene expression (thor)

fineST(image_path, name[, spot_adata_path, ...])

Class for in silico cell gene expression inference

`pp.WholeSlideImage`(image_path[, name, ...])	Whole slide image class.
`pp.Spatial`(name, st_dir[, image_path, save_dir])	Class for spatial transcriptomics data.

`pp.preprocess_image`(image_path[, bbox, ...])	Preprocess the image and extract features from the cells.
`pp.load_nuclei`([nuclei_path, source_format])	Load nuclei segmentation result from a file.
`pp.load_cellpose`(nuclei_path)	Load nuclei segmentation result from a cellpose output file.
`pp.load_cellprofiler`(nuclei_path)	Load nuclei segmentation result from a cellprofiler output file.
`pp.load_mask_npz`(nuclei_path)	Load nuclei segmentation result from a mask array npz file.
`pp.nuclei_segmentation`(image_path[, ...])	Segment nuclei from H&E stained images using stardist, cellpose or histocartography.

`pl.single`(var_name, img_mask[, ax, vor, ...])	Color the cells or nuclei with one variable, gene name, or any other observable (prepared img_mask as input).
`pl.multiple`(vars_list, img_masks_list[, ax, ...])	Color the cells or nuclei with multiple variables, gene or any observable (prepared `img_mask`s as input).
`pl.single_molecule`(var, var_expression, ...)	Color the cells or nuclei with a variable, gene or any observable (gene expression vector as input).
`pl.multi_molecules`(vars_list, ...[, ...])	Color the cells or nuclei with multiple variables, gene or any observable (gene expression array as input).
`pl.clusters`(cluster_labels_list[, ...])	Color the cells or nuclei with cluster labels.
`pl.spot_over`(ad, ad_spot[, spot_scale, ...])	Plot spatial expression data with spots on top.
`pl.annotate_ROI`(im[, ROI_polygon, ...])	Annotate the ROI and baseline on the image.
`pl.deg`([data, genes, baseline_from_edge, ...])	Plot log2foldchange of gene expression against distance from the baseline.

analy.SPARKX([rscript_path])

Class for running SPARKX.

`analy.analyze_gene_expression_gradient`(adata)	Analyze gene expression against a baseline in a selected region of interest (ROI).
`analy.compute_dge_between_regions`(ad_r1, ad_r2)	Compute differential gene expression (DGE) between two regions.
`analy.get_pathway_score`(adata[, layer, ...])	Calculate pathway score for each cell using over-representation analysis.
`analy.get_tf_activity`(adata[, layer, ...])	Infer TF activity using the CollecTRI database.
`analy.read_polygon_ROI`(json_path, adata[, ...])	Read polygon ROI from json file.
`analy.prepare_and_run_copykat`(adata[, ...])	Run CopyKAT on the input data.
`analy.adata_to_mtx_conversion`(adata[, ...])	Convert AnnData object to matrix market format.
`analy.run_commot`(adata[, region, ...])	Run the cell-cell communication analysis using the modified COMMOT method.