MATRICS-A

Code for "Human Digital Twin: 3D Atlas Reconstruction of Skin and Spatial Mapping of Immune Cell Density, Vascular Distance and Effects of Sun Exposure and Aging"

Soumya Ghose^1,2, Yingnan Ju^1,3, Elizabeth McDonough²,Jonhan Ho⁴, Arivarasan Karunamurthy⁴, Chrystal Chadwick², Sanghee Cho², Rachel Rose², Alex Corwin², Eric Williams², Christine Surrette², Jessica Martinez², Anup Sood², Yousef Al-Kofahi², Louis Falo⁴, Katy Börner^3,5, Fiona Ginty^2,5

¹Joint first-authors; ⁵Joint corresponding authors
²GE Research Center; ³Indiana University; ⁴University of Pittsburgh

Link to preprint on bioRxiv
VCCF visualization for skin in 3D
Link to VCCF code on GitHub
Link to Data Collection on HuBMAP Portal

MATRICS-A

Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial -Analysis

1. Create folder $YOUR_WORKING_DIRECTORY
2. Pull docker container: docker pull hubmap/gehc:skin from $YOUR_WORKING_DIRECTORY
3. Please download data from: https://zenodo.org/record/7565670#.Y9EoSS-B2-p and create folder $YOUR_WORKING_DIRECTORY/DATA/region007. Extract all zipped folders (AF, AE, CD3 etc.) under DATA/region007
4. Clone repository from MATRICS-A
5. Load docker container: nvidia-docker run --rm -it -v $YOUR_WORKING_DIRECTORY hubmap/gehc:skin
6. Run shell script to segment all cells (CD3, CD4 etc.) and nuclei (DAPI) of DATA/region007 from docker prompt: ./MATRICS-A/SCRIPTS/Segmentation.sh. This script segments DAPI (nuclei segmentation), use Gaussian mixture model to assign probablistic segmentation of cell types and functional biomarkers and combines probabilities for cell classification.
7. Run shell script to register all autofluorescence (AF) images and create 3D volume for AF images and respective cell types:./MATRICS-A/SCRIPTS/Registration.sh. This script automatically registers all 2D AF images of region 7 to a pre-selected 2D AF image to create 3D reconstructed AF image volume. The transformation maps post registration are automatically applied to cell types and functional biomarkers to create 3D reconstructed volumes of individual cell-type (i.e., epithelial, immune) and DNA damage/repair and proliferation markers (i.e., p53, DDB2, Ki67).
8. AF and other cell volumes will be created under individual folders (AF, CD4 etc.) as AF_vol.nii.gz, CD4(THelper_vol.nii.gz), CD8(TKiller_vol.nii.gz), FOXP3(TRegulator_vol.nii.gz), Blood vessels(CD31_vol.nii.gz), Macrophages (CD68_vol_Proc.nii.gz), DDB2(DDB2_vol.nii.gz), KI67 (KI67_vol.nii.gz).
9. Run ./MATRICS-A/SCRIPTS/3DCoordinates.sh to generate 3D coordinates of cell types and functional biomarkers as csv files under individual folders.
10. Use 3D Slicer (https://www.slicer.org) load AF and other volumes overlay on top of the AF volume to visualize all in 3D.

System used for running the code: Docker version 19.03.12, Ubuntu 18.04.6 LTS, NVIDIA Driver Version: 418.67, CUDA Version: 10.1.