Cellular state often exists in a continuum rather than distinct phases. A prime example is cell development and differentiation. With single-cell RNA-Seq, researchers can observe this continuum of transcriptomic changes via analysis of individual cells. The need to computationally model these dynamics leads to the birth of single-cell RNA-seq trajectory […]
Differential expression analysis is a common step in a Single-cell RNA-Seq data analysis workflow. In our previous post, we have given an overview of differential expression analysis tools in single-cell RNA-Seq. This time, we’d like to discuss a frequently used tool – DESeq2 (Love, Huber, & Anders, 2014). According to […]
In the previous post, we talked about how to visualize single-cell RNA Sequencing (scRNA-seq) data to gain meaningful insights. But there are many steps from raw sequencing data to such beautiful visualization (and further analysis) that decide whether or not researchers can make sense of their data. They include preprocessing […]
How to Make Sense of Single-cell RNA Sequencing Data? Less is More Thanks to single-cell RNA sequencing (scRNA-seq), researchers are blessed with a trove of information. Yet, this blessing is also a curse in data visualization and further analysis! Since each cell is described by its gene expression profile, our […]
Multiple studies have shown smoking’s effects on the human bronchi. However, few have characterized its precise impact at cellular resolution. Published recently on Science Advances, a study by Duclos and colleagues has employed single-cell RNA sequencing into exploring the cellular changes in the human bronchial epithelium between current and never […]
Single-cell RNA-seq technologies have opened up a completely new era for transcriptomic studies. For the first time ever, scientists can look at individual transcriptomic profiles of millions of cells, and better understand how each cell functions in a tissue. Yet science is confronting bigger challenges analyzing these massive amounts of […]
