Python package to measure the similarity between matched single cell and targeted spatial transcriptomics data
In a clean conda
environment with pip installed, run in the terminal:
git clone https://github.com/theislab/txsim.git
Navigate to the folder:
cd txsim
And install using pip
:
pip install -e .
To import txsim
, install squidpy
(and all of its dependencies) into your environment
For full functionality, the following are required as well:
alphashape
descartes
pciSeq
cellpose
All of the functions in txsim are currently either in the metrics
or preprocessing
module.
A list of functions is as follows:
coexpression_similarity
coexpression_similarity_celltype
all_metrics
- Normalization:
normalize_total
,normalize_pearson_residuals
,normalize_by_area
- Segmentation:
segment_nuclei
,segment_cellpose
- Assignment:
basic_assign
,run_pciSeq
- Count Generation:
generate_adata
,calculate_alpha_area