Single-Cell RNAseq Complexity Reduction

Francesca Cordero; Raffaele A Calogero

doi:10.1007/978-1-0716-2756-3_10

Single-Cell RNAseq Complexity Reduction

Methods Mol Biol. 2023:2584:217-230. doi: 10.1007/978-1-0716-2756-3_10.

Authors

Francesca Cordero¹, Raffaele A Calogero²

Affiliations

¹ Department of Computer Science, University of Torino, Turin, Italy.
² Molecular Biotechnology Center, University of Torino, Torino, Italy. raffaele.calogero@unito.it.

PMID: 36495452
DOI: 10.1007/978-1-0716-2756-3_10

Abstract

An important step in single-cell RNAseq data analysis is the preparation of the single cell transcription data for cell sub-population partitioning. In this chapter, we describe how to perform complexity reduction for 3' end single-cell RNAseq transcriptomics data.

Keywords: Data preprocessing; Dimensionality reduction; Single cell transcriptomics.

MeSH terms

Gene Expression Profiling*
Sequence Analysis, RNA
Single-Cell Analysis
Single-Cell Gene Expression Analysis*