Mass Cytometry, 1st ed. 2019 Methods and Protocols Methods in Molecular Biology Series, Vol. 1989

This book details up-to-date and cutting edge compilation of protocols in mass cytometry. Chapters guide readers through setting up a facility, panel design and reagent preparation, sample preparation, specific applications, and data analysis. 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.

Authoritative and cutting-edge, Mass Cytometry: Methods and Protocols aims to ensure successful results in the further study of this vital field.

Setting up Mass Cytometry in a Shared Resource Lab Environment.- Acquisition, Processing, and Quality Control of Mass Cytometry Data.- Visualization of Mass Cytometry Signal Background to Enable Optimal Core Panel Customization and Signal Threshold Gating.- Method for Tagging Antibodies with Metals for Mass Cytometry Experiments.- Scalable Conjugation and Characterization of Immunoglobulins with Stable Mass Isotope Reporters for Single-Cell Mass Cytometry Analysis.- Titration of Mass Cytometry Reagents.- Cell-Surface Barcoding of Live PBMC for Multiplexed Mass Cytometry.- Automated Cell Processing for Mass Cytometry Experiments.- Live Cell Barcoding for Efficient Analysis of Small Samples by Mass Cytometry.- Staining of Phosphorylated Signalling Markers Protocol for Mass Cytometry.- Multiplex MHC Class I Tetramer Combined with Intranuclear Staining by Mass Cytometry.- Analysis of the Murine Bone Marrow Haematopoietic System Using Mass and Flow Cytometry.- Mass Cytometric Cell Cycle Analysis.- Picturing Polarized Myeloid Phagocytes and Regulatory Cells by Mass Cytometry.- Quantitative Measurement of Cell-nanoparticle Interactions Using Mass Cytometry.- Data-Driven Flow Cytometry Analysis.- Analysis of Mass Cytometry Data.- Analysis of High Dimensional Phenotype Data Generated by Mass Cytometry or High Dimensional Flow Cytometry.- Computational Analysis of High Dimensional Mass Cytometry Data from Clinical Tissue Samples.- Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery.