Skip to content

BiomedicalMachineLearning/SkinSpatial

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

86 Commits
 
 
 
 
 
 
 
 

Repository files navigation

SkinSpatial is a repository for the code to analyse skin spatial data. Here we host an official version and development of STRISH (Spatial Transcriptomic and RNA In-situ Hybridization) pipeline.

STRISH pipeline documentation

STRISH is a computational pipeline that enables us to quantitatively model cell-cell interactions by automatically scanning for local expression of RNAscope data to recapitulate an interaction landscape across the whole tissue.

STRISH pipeline consists of three major steps.

Step 1: Run cell detection for RNAScope data using series of nonoverlapped windows with QuPath. The size of scanning windows are initially set to 10% (customizable) of the whole scan image. If the cell detection result in the current window is greater than the threshold, gradually split the window size into smaller subwindow until the conditions are satisfied (window). Otherwise, remove the window from the current list of scanning windows. The cell detection algorithm pseudocode is followed pseudocode

drawing

More illustrations about STRISH cell detection with the windows strategy can be found here

Step 2: Run a Python process to computationally quantify ligand-receptor local co-expression level of two pairs of target markers. STRISH pipeline iterates all the detection results from previous step and considers every window that cells express both ligand and receptor marker. Otherwise, the coexpression score for the windows is set to 0. For the pair of ligand-receptor which two markes come from two separated scanning image, image registration is required before evaluating local co-expression level in the tissue. The final outcome is visualize by the heatmap.

drawing

Step 3: Cropping background and plotting tissue contour to focus on the main tissue area, i.e. Fig 3.

Additional analysis

  1. For details about cell-cell interation analysis with Visium data, visit stLearn github page at stLearn
  2. For CellPhoneDB method for ligand-receptor interaction prediction, visit CellPhoneDB github page CellPhoneDB
  3. NicheNet analysis with Seurat object for cell-cell interaction was used following vignette: NicheNet

Examples of STRISH analysis of RNAscope data:

  1. RNAscope scanned image with five markers Merged image

  2. RNAscope scanned image with five markers

drawing

  1. Heatmap of Ligand-receptor communication for the pair of CSF1R and IL34 LR interation

About

A repository for the code to analyse skin spatial data

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages