Single Cell Transcriptomics: Methods and Protocols (Methods in Molecular Biology #2584) (Hardcover)

Single Cell Transcriptomics: Methods and Protocols (Methods in Molecular Biology #2584) By Raffaele A. Calogero (Editor), Vladimir Benes (Editor) Cover Image

Single Cell Transcriptomics: Methods and Protocols (Methods in Molecular Biology #2584) (Hardcover)

By Raffaele A. Calogero (Editor), Vladimir Benes (Editor)


Not On Our Shelves—Ships in 1-5 Days

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

Katharina Danielski

2. BD Rhapsody(TM) 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 J rg 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 Corderoand 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

Product Details ISBN: 9781071627556
ISBN-10: 1071627554
Publisher: Humana
Publication Date: December 11th, 2022
Pages: 390
Language: English
Series: Methods in Molecular Biology