Beyond bulk: a review of single cell transcriptomics methodologies and applications.
Single-cell RNA sequencing (scRNA-seq) is a promising approach to study the transcriptomes of individual cells in the brain and the central nervous system (CNS). This technology acts as a bridge between neuroscience, computational biology, and systems biology, enabling an unbiased and novel understanding of the cellular composition of the brain and CNS. Gene expression at the single cell resolution is often noisy, sparse, and high-dimensional, creating challenges for computational analysis of such data. In this review, we overview fundamental sample preparation and data analysis processes of scRNA-seq and provide a comparative perspective for analyzing and visualizing these data.
1. Breathing fresh air into respiratory research with single-cell RNA sequencing.
2. Single-cell and spatial transcriptomics approaches of cardiovascular development and disease.
3. From Bite to Byte: Dental Structures Resolved at a Single-Cell Resolution.
4. Advances and Opportunities in Single-Cell Transcriptomics for Plant Research.
5. Single Cell Gene Expression to Understand the Dynamic Architecture of the Heart.
1. The comparison of high-throughput single-cell RNA-seq methods
2. Droplet barcoding for single cell transcriptomics applied to embryonic stem cells
3. Single-Cell Analysis of Sensory Experience Regulated Gene Expression in Mouse Visual Cortex
4. Detecting Activated Cell Populations Using Single-Cell RNA-Seq
5. Single-cell RNA-Seq reveals a developmental atlas of human prefrontal cortex