Abstract
Single-cell RNA sequencing (scRNA-seq) experiment reveals previously unseen molecular features. The number of sequencing procedures and computational data analysis approaches has been increasing rapidly in recent years. This chapter provides a general idea of the single-cell data analysis and visualization. An introduction and practical guidance for the 10× sequencing data analysis and visualization are presented. Basic data analysis approaches are highlighted, followed by quality control of data, filtering in cell level and gene level, normalization, dimensional reduction, clustering analysis, and marker identification.
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The authors would like to thank Chen **aoni and Juthika (University of Missouri, Columbia, Missouri, USA) for her language assistance.
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Saddala, M.S., Mundla, S., Patyal, N., Dash, S. (2023). Single-Cell RNA Sequencing (scRNA-Seq) Data Analysis of Retinal Homeostasis and Degeneration of Microglia. In: Liu, GS., Wang, JH. (eds) Diabetic Retinopathy. Methods in Molecular Biology, vol 2678. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3255-0_6
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DOI: https://doi.org/10.1007/978-1-0716-3255-0_6
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