Abstract
Single-cell RNA sequencing provides a new approach to an old problem: how to study cellular diversity in complex biological systems. This powerful tool has been instrumental in profiling different cell types and investigating, at the single-cell level, cell states, functions, and responses. However, mining these data requires new analytical and statistical methods for high-dimensional analyses that must be customized and adapted to specific goals. Here we present a custom multistage analysis pipeline which integrates modules contained in different R packages to ensure flexible, high-quality RNA-seq data analysis. We describe this workflow step by step, providing the codes, explaining the rationale for each function, and discussing the results and the limitations. We apply this pipeline to analyze different datasets of Drosophila larval ventral cords, identifying and describing rare cell types, such as astrocytes and neuroendocrine cells. This multistage analysis pipeline can be easily implemented by both novice and experienced scientists interested in neuronal and/or cellular diversity beyond the Drosophila model system. © 2021 US Government.