User Guide

zoom dedicates to provide a Python platform for integrating multimodal, multiscale neuro‑omics data types. In our present work, we have successfully linked spatial brain phenotypes (SBPs), the anatomically comprehensive Allen Human Brain Atlas (AHBA), and single‑cell RNA sequencing (scRNA-seq) datasets.

This user guide describes, in sequence, how to preprocess the above data types with zoom, implement the imaging‑transcriptomics paradigm which associate SBPs with AHBA, and finally compute single‑cell enrichment scores for SBP‑relevant gene sets. If you have further questions, please consult API Documents or submit an issue on GitHub.

Table of Contents

• Prepare input data
  • The Allen Human Brain Atlas dataset
  • The spatial brain phenotype data
  • The single-cell RNA sequencing data
• Imaging-transcriptomics
  • Construct main class of zoom
  • Partial least squares regression
  • Gene contribution statistics
  • Pick optimally sized gene set
  • Spatial permutation-based GSEA
• Single-cell enrichment score of SBP-relevant gene set
  • Single-cell scoring
  • Downstream analyses