Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021:2284:289-301.
doi: 10.1007/978-1-0716-1307-8_16.

Computational Analysis of Single-Cell RNA-Seq Data

Luca Alessandrì  1 , Francesca Cordero  2 , Marco Beccuti  2 , Maddalena Arigoni  1 , Raffaele A Calogero  3
Affiliations

Computational Analysis of Single-Cell RNA-Seq Data

Luca Alessandrì et al. Methods Mol Biol. 2021.

Abstract

Single-cell RNAseq data can be generated using various technologies, spanning from isolation of cells by FACS sorting or droplet sequencing, to the use of frozen tissue sections retaining spatial information of cells in their morphological context. The analysis of single cell RNAseq data is mainly focused on the identification of cell subpopulations characterized by specific gene markers that can be used to purify the population of interest for further biological studies. This chapter describes the steps required for dataset clustering and markers detection using a droplet dataset and a spatial transcriptomics dataset.

Keywords: Bioinformatics; Cell markers; Clustering; Droplet; Single cell RNA sequencing; Spatial transcriptomics.

PubMed Disclaimer

References

    1. Ziegenhain, C., et al., (2017) Comparative analysis of single-cell RNA sequencing methods. Mol Cell, 2017. 65(4): 631–643.e4
    1. Gross A et al (2015) Technologies for Single-Cell Isolation. Int J Mol Sci 16(8):16897–16919 - DOI
    1. Lecault V et al (2012) Microfluidic single cell analysis: from promise to practice. Curr Opin Chem Biol 16(3–4):381–390 - DOI
    1. Picelli S et al (2014) Full-length RNA-seq from single cells using smart-seq2. Nat Protoc 9(1):171–181 - DOI
    1. Macosko EZ et al (2015) Highly parallel genome-wide expression profiling of individual cells using Nanoliter droplets. Cell 161(5):1202–1214 - DOI

MeSH terms

LinkOut - more resources