Methods in Molecular Biology
Contaldo, Sandro G.; Alessandri, Luca; Colonnelli, Iacopo; Beccuti, Marco; Aldinucci, Marco
The idea behind novel single-cell RNA sequencing (scRNA-seq) pipelines is to isolate single cells through microfluidic approaches and generate sequencing libraries in which the transcripts are tagged to track their cell of origin. Modern scRNA-seq platforms are capable of analyzing up to many thousands of cells in each run. Then, combined with massive high-throughput sequencing producing billions of reads, scRNA-seq allows the assessment of fundamental biological properties of cell populations and […]
Methods in Molecular Biology
Beccuti, Marco; Calogero, Raffaele A.
Single-cell RNA sequencing (scRNA-seq) allows the creation of large collections of individual cells transcriptome. Unsupervised clustering is an essential element for the analysis of these data, and it represents the initial step for the identification of different cell types to investigate the cell subpopulation organization of a sample. In this chapter, we describe how to approach the clustering of single-cell RNAseq transcriptomics data using various clustering tools, and we provide some information […]
Methods in Molecular Biology
Cordero, Francesca; Calogero, Raffaele A.
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.
Methods in Molecular Biology
Contaldo, Sandro G.; Alessandri, Luca; Colonnelli, Iacopo; Beccuti, Marco; Aldinucci, Marco
The idea behind novel single-cell RNA sequencing (scRNA-seq) pipelines is to isolate single cells through microfluidic approaches and generate sequencing libraries in which the transcripts are tagged to track their cell of origin. Modern scRNA-seq platforms are capable of analyzing up to many thousands of cells in each run. Then, combined with massive high-throughput sequencing producing billions of reads, scRNA-seq allows the assessment of fundamental biological properties of cell populations and […]
Methods in Molecular Biology
Beccuti, Marco; Calogero, Raffaele A.
Single-cell RNA sequencing (scRNA-seq) allows the creation of large collections of individual cells transcriptome. Unsupervised clustering is an essential element for the analysis of these data, and it represents the initial step for the identification of different cell types to investigate the cell subpopulation organization of a sample. In this chapter, we describe how to approach the clustering of single-cell RNAseq transcriptomics data using various clustering tools, and we provide some information […]
Methods in Molecular Biology
Cordero, Francesca; Calogero, Raffaele A.
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.