DOI: 10.6084/m9.figshare.16663465
title: A spatially resolved timeline of the human maternal-fetal interface

description: <br><b>Data files provided</b><br>denoised.zip,denoised1.zip: denoised MIBI images for the entire cohort. The images are divided into two archive files due to uploading file size limitations - we apologize for the inconvenience. The files are organized by field of view (FOV), with each FOV subfolder containing TIF images for each channel that have undergone low-level processing as described in the methods section “Low-level image processing”.mask_labeled.zip: labeled feature annotations for the entire cohort. These are organized by FOV, with each FOV subfolder containing individual TIFs for each annotated feature (arteries, vessels, glands) in the image (see Methods section “Feature annotation”). Features in each TIF have been assigned a unique label for downstream analyses.lineage_CPMs_for_cohort.zip: contains cell phenotype map (CPM) pseudo color overlays for the entire cohort. These are labeled by FOV, and each FOV shows the cell segmentation mask colored by cell lineage assignment (see Methods).cell_cell_and_cell_artery_spatial_enrichment_per_image.zip - cell-cell and cell-artery enrichment z-scores per image (see Methods)Single_cells_MIBI.csv.zip - a table enumerating all single cells in this study and provides their location, morphological characteristics (such as size and shape), marker expression, FlowSOM cluster assignment and cell type assignmentSegmentation.zip: segmentation results per FOV, pixels value in each cell correspond to the cell label in the single cell table. <b>Code</b>The code in the “Code” folder is divided into three subfolders as follows:<br>Digitized artery morphology - MATLAB code for digitized measurement of artery morphological features from MIBI images and corresponding artery masks (see Methods section “Automated digitization of artery morphological features”). The code requires user input - marking the center of each analyzed artery via GUI. For running this code, download data folders mask_labeled.zip then download and recombine into a single folder the content of the archive files denoised.zip, denoised1.zip. Required additional software: MAUI - freely available at https://github.com/angelolab/MAUI. Start by opening the code file “MAIN_script_start_here.m”, further running instructions are at the head of this file. For expected output see Supplemental Table 3 in the manuscript.Remodeling score delta calculation - MATLAB and R code for calculating the remodeling score per artery (see Methods section “Calculation of continuous SAR remodeling score δ”). Start by opening the code file “MAIN_script_Prepare_LDA_table_calc_delta.m”, further running instructions are at the head of this file. The input table for this code is inside it's subfolder (artery properties table generated by code in #1 above- artery_staging_input.mat) and none of the data folders are required to run. For expected output see Supplemental Table 3 in the manuscript.Code for generating LDA of EVT by compartment (see Methods) - R code for calculating ld1 per EVT, see Methods section “LDA of EVTs by compartment”). The input table for this code - z-scored marker expression in all EVT (EVT_markers_for_LDA,csv), is inside it's subfolder and none of the data folders are required to run. For expected output see Supplemental Tables 19,20 in the manuscript.MATLAB code was written and tested on MATLAB 2020b and MAC OS Catalina Version 10.15.7. R code was tested on R version 4.0.3 MAC OS Catalina Version 10.15.7, code was written using the following versions:<br>R 3.5.1RStudio 1.1.463MASS_7.3-51.5dplyr_0.8.3data.table_1.12.8Estimated runtime for code in above enumerated folders:Depends on manual user input, estimated at a few minutes per arteryMATLAB parts run instantaneously while R script for LDA can take approximately 30 minutes.R script for LDA can take approximately 30 minutes.