The single-cell analyses will allow researchers to uncover new and potentially unexpected biological discoveries relative to traditional profiling methods that assess bulk populations. This tutorial is to provide an overview of the laboratory and computational method involved in generating and analyzing single cell data. Participants will be introduced to the workflow of single cell analysis, the principles of single cell platforms, including Fluidigm C1/ Biomark, 10xGenomics, BD Rhapsody, and iCell8, and will focus on different solutions of 10xGenomics. The tutorial will introduce the main computational algorithms and tools for single cell data analysis, including demultiplexing sequence alignment, quality control, identifying clusters of cells and performing analyses to assign cell identity and function. We will also give an introduction of single-cell RNA sequencing in immunology and use Loupe browser to show how to work with single cell V(D)J seq data. There will be a hands-on case study on single cell RNAseq data analysis. Analyses will be performed by using Seurat in R interfaces.