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Kernel-Bounded-Clustering-for-Spatial-Transcriptomics

Installation

python 3.8+

    pip install scikit-learn
    pip install h5py
    pip install pandas
    pip install python-igraph
    pip install scanpy

Matlab install the toolbox:

  1. Parallel Computing Toolbox
  2. Statistics and Machine Learning Toolbox

Dataset

The datasets in the turtorial are already preprocessed, download it from the following link and move it to the current directory tutorial/Dataset

https://drive.google.com/drive/folders/1MziiMAcUQeXwX8kvKaYmmoZBkzmohrlH?usp=drive_link

and the original dataset can be downloaded from the following link.

DLPFC

http://spatial.libd.org/spatialLIBD/

HER2st

https://github.com/almaan/her2st

Slide-seq V2 mouse hippocampus

https://singlecell.broadinstitute.org/single_cell/study/SCP815/sensitive-spatial-genome-wideexpression-profiling-at-cellular-resolution#study-summary

Stereo-seq mouse olfactory bulb

https://github.com/JinmiaoChenLab/SEDR_analyses

DLPFC

  1. cd /tutorial/wlikbc
  2. Run DLPFC_WL.py
  3. Open Matlab and run the file turtorial/KBC/DLPFC_KBC.m

HER2st

  1. cd /tutorial/wlikbc
  2. Run HER2stWL.py
  3. Open Matlab and run the file turtorial/KBC/HER2st_KBC.m

Slide-seq V2 mouse hippocampus

  1. cd /tutorial/wlikbc
  2. Run slideseqv2norwl.py
  3. Open Matlab and run the file turtorial/KBC/Slideseqv2_KBC.m

Stereo-seq mouse olfactory bulb

  1. cd /tutorial/wlikbc
  2. Run sterseqwl.py
  3. Open Matlab and run the file turtorial/KBC/sterseq_KBC.m
  4. cd /tutorial/wlikbc and run plot_stereo.py