Computational Analysis of Single-Cell RNA-Seq Data

Abstract

Single-cell RNA sequencing (scRNA-seq) is gaining popularity as this allows you to profile a large number of individual cells. However, as the volume of the data increases, the need for appropriate computational methods also arises. Here, I will provide an overview of standard computational workflow for scRNA-seq and discuss each step and provide useful tips if applicable.

Keywords: Batch effect; Normalization differential expression; Single-cell RNA sequencing (scRNA-seq); Unique molecular identifier (UMI).