Processed Data for: Multi-Modal Profiling of Alzheimer's Disease: From Dual Molecular Signatures to Neuropathology-Predominant Cognitive Prediction

This repository contains the processed data required to reproduce the key findings of the manuscript "Multi-Modal Profiling of Alzheimer’s Disease: From Dual Molecular Signatures to Neuropathology-Predominant Cognitive Prediction". The data is organized into four main categories corresponding to the core analyses of the paper: Cell Composition: A cell-level metadata file (omics_data(class&sub).csv) containing the class, subclass, and cognitive status annotation for every cell, used for the initial cell composition overview analysis (Figure 1). Machine Learning: A single CSV file (donor_level_feature_matrix.csv) containing the final, donor-level aggregated feature matrix used for all predictive modeling. Differential Expression: Five CSV files containing the full statistical results for significantly differentially expressed genes (DEGs) for each of the five analyzed cell subclasses. A background gene list for functional enrichment analysis is also provided. Spatial Analysis: A single CSV file (merfish_for_r_analysis.csv) containing the pre-processed MERFISH data, including cell coordinates and metadata, used as input for the statistical models in R. Please refer to the original publication and the associated GitHub repository for the code used to generate and analyze this data.