
Single Cell Transcriptomics
Methods and Protocols
Springer (Publisher)
Published on 11. December 2022
Book
Hardback
XI, 390 pages
978-1-0716-2755-6 (ISBN)
Description
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.
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.
More details
Series
Edition
2023 ed.
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Illustrations
5 s/w Abbildungen, 121 farbige Abbildungen
XI, 390 p. 126 illus., 121 illus. in color.
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 28 mm
Weight
954 gr
ISBN-13
978-1-0716-2755-6 (9781071627556)
DOI
10.1007/978-1-0716-2756-3
Schweitzer Classification
Other editions
Additional editions

Book
12/2023
Springer
€165.84
Shipment within 15-20 days

E-Book
12/2022
Humana
€160.49
Available for download
Content
Guidance on processing the 10x Genomics Single Cell Gene Expression Assay.- BD RhapsodyT Single-Cell Analysis System Workflow: From sample to multimodal single cell sequencing data.- Profiling transcriptional heterogeneity with Seq-Well S
3
: A low-cost, portable, high-fidelity platform for massively-parallel single-cell RNA-seq.- A MATQ-seq based protocol for single-cell RNA-seq in bacteria.- Full-length single-cell RNA-sequencing with FLASH-seq.- Plant single cell/nucleus RNA-seq workflow.- Ensuring Quality Cell Input for Single Cell Sequencing Experiments by Viability and Singlet Enrichment using Cell Sorting.- Tissue RNA integrity in Visium Spatial Protocol (Fresh Frozen Samples).- Single cell RNAseq data QC and preprocessing.- Single cell RNAseq complexity reduction.- Functional-feature-based data reduction using sparsely connected autoencoders.- Single cell RNAseq clustering.- Identifying Gene Markers AssociatedTo Cell Subpopulations.- A guide to trajectory inference and RNA velocity.- Integration of scATAC-seq with scRNA-seq data.- Using "Galaxy-rCASC", a public Galaxy instance for single-cell RNA-Seq data analysis.- Bringing cell subpopulation discovery on a cloud-HPC using rCASC and StreamFlow.- Profiling RNA editing in single cells.