Single Cell Transcriptomics: Methods and Protocols

ISBN-13: 9781071627556 / Angielski / Twarda / 2022 / 390 str.

Raffaele A. Cologero; Vladimir Benes

Opis

This volume provides up-to-date methods on single cell wet and bioinformatics protocols based on the researcher experiment requirements. Chapters detail basic analytical procedures, single-cell data QC, dimensionality reduction, clustering, cluster-specific features selection, RNA velocity, multi-modal data integration, and single cell RNA editing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Cutting-edge and comprehensive, Single Cell Transcriptomics: Methods and Protocols aims to be a valuable resource for all researchers interested in learning more about this important and developing field.

Spis treści

1. Guidance on processing the 10x Genomics Single Cell Gene Expression Assay

Katharina Danielski

 

2. BD Rhapsody™ Single-Cell Analysis System Workflow: From sample to multimodal single cell sequencing data

Jannes Ulbrich, Vadir Lopez-Salmeron, and Ian Gerrard

 

3.  Profiling transcriptional heterogeneity with Seq-Well S³: A low-cost, portable, high-fidelity platform for massively-parallel single-cell RNA-seq

 

Riley S Drake, Martin Arreola Villanueva, Mike Vilme, Daniela D Russo, Andrew Navia, J. Christopher Love, and Alex K. Shalek

 

4. A MATQ-seq based protocol for single-cell RNA-seq in bacteria

Christina Homberger, Antoine-Emmanuel Saliba, and Jörg Vogel

 

5. Full-length single-cell RNA-sequencing with FLASH-seq

Vincent Hahaut and Simone Picelli

 

6. Plant single cell/nucleus RNA-seq workflow

Sandra Thibivilliers, Andrew Farmer, Susan Schroeder, and Marc Libault

 

7. Ensuring Quality Cell Input for Single Cell Sequencing Experiments by Viability and Singlet Enrichment using Cell Sorting

Malte Paulsen

 

8. Tissue RNA integrity in Visium Spatial Protocol (Fresh Frozen Samples)

Federica Antico, Marta Gai, and Maddalena Arigoni

 

9. Single cell RNAseq data QC and preprocessing

Martina Olivero and Raffaele A Calogero

 

10. Single cell RNAseq complexity reduction

Francesca Cordero and Raffaele A Calogero

 

^11. Functional-feature-based data reduction using sparsely connected autoencoders

Luca Alessandri and Raffaele A Calogero

 

12. Single cell RNAseq clustering

Marco Beccuti and Raffaele A Calogero

 

13. Identifying Gene Markers Associated To Cell Subpopulations

Maria Luisa Ratto and Luca Alessandri

 

14. A guide to trajectory inference and RNA velocity
Philipp Weiler, Koen Van den Berge, Kelly Street, and Simone Tiberi

15. Integration of scATAC-seq with scRNA-seq data

Ivan Berest and Andrea Tangherloni

 

16. Using “Galaxy-rCASC”, a public Galaxy instance for single-cell RNA-Seq data analysis

Pietro Mandreoli, Luca Alessandri, Raffaele A. Calogero, Marco Antonio Tangaro, Federico Zambelli

 

17. Bringing cell subpopulation discovery on a cloud-HPC using rCASC and StreamFlow

Sandro G. Contaldo, Luca Alessandri, Iacopo Colonnelli, Marco Beccuti and Marco Aldinucci

 

18. Profiling RNA editing in single cells

Adriano Fonzino, Graziano Pesole, and Ernesto Picardi