Variations in gene expression among different organisms, tissues, and disease states have traditionally been quantified using techniques like in situ hybridization (ISH), microarrays, or total RNA sequencing (RNA-seq). These methods suffer from limitations such as low throughput for ISH or providing only average measurements across cell populations. The advent of single cell transcriptomic technologies, like Chromium Single Cell Gene Expression, enables direct measurements of gene expression at the individual cell level, allowing for a comprehensive assessment of cell population heterogeneity. Download this guide now for information on how to design your experiments effectively, optimize crucial experimental parameters, and identify appropriate computational and analytical tools to thoroughly analyze your single cell gene expression data.