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. 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.

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