Cellular Spatial Characterization and Analysis
Description
This volume covers the latest advancements in staining techniques, and protocols and process data using various bioinformatic approaches. The chapters in this book are divided into broad themes of traditional immunohistochemistry, advanced spatial proteomics, and spatial genomics. Written in the highly successful
Methods in Molecular Biology
series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Comprehensive and cutting-edge,
Cellular Spatial Characterization and Analysis
is a valuable resource for any researchers looking to learn more about this developing field.
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Content
1. High-Plex Tissue Imaging with Conventional Immunofluorescence Platforms and Open-Source Software via Iterative Bleaching Extends Multiplexity (IBEX).- Multiplex Immunofluorescence Staining of Paraffin-Embedded Tissue: Coverslip Mounting of Tissue Sections Improves Z-axis Optical Resolution in Widefield Microscopy.- Evaluation of Murine Tissue Architecture and Cellular Spatial Relationships in Murine Tumor Microenvironments Utilizing Multiplex Fluorescent Immunohistochemistry.- Autostaining Immune Multiplex Immunohistochemistry Panels and Imaging Analysis.- Fully Integrated Sample Preparation-Based Spatial Proteomic Analysis.- Detailed Protocol for Expansion of Large Tissue Samples for Expansion Microscopy.- Current Methods in CODEX High-Multiplex Microscopy to Describe Spatial Relationships in the Tissue Microenvironment.- Mapping the Tumor Microenvironment with Integrative Single-Cell RNA Sequencing and Spatial Proteomics: Uncovering Mechanisms of Disease and Therapeutic Resistance.- Single-Molecule Fluorescence In Situ Hybridization (smFISH) for RNA Localization Relative to a DNA Locus in Bacteria.- A Protocol for Spatial Transcriptomics using the 10x Genomics Visium Platform.- Highly Multiplexed Single-Cell In Situ RNA and DNA Analysis by Consecutive Hybridization.- From Raw Data to Biological Insights: A Practical Guide for Spatial Transcriptomics Analysis in R and Python.