Single Cell Transcriptomics

Methods and Protocols

Raffaele A. Calogero, Vladimir Benes (Herausgeber)

Buch | Hardcover

390 Seiten

2022 | 1st ed. 2023
Springer-Verlag New York Inc.
978-1-0716-2755-6 (ISBN)

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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.

Guidance on processing the 10x Genomics Single Cell Gene Expression Assay.- BD Rhapsody™ Single-Cell Analysis System Workflow: From sample to multimodal single cell sequencing data.- Profiling transcriptional heterogeneity with Seq-Well S3: 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.

Erscheinungsdatum	14.12.2022
Reihe/Serie	Methods in Molecular Biology ; 2584
Zusatzinfo	121 Illustrations, color; 5 Illustrations, black and white; XI, 390 p. 126 illus., 121 illus. in color.
Verlagsort	New York, NY
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Informatik ► Weitere Themen ► Bioinformatik
	Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
	Naturwissenschaften ► Biologie ► Mikrobiologie / Immunologie
	Naturwissenschaften ► Biologie ► Zellbiologie
Schlagworte	CITE-seq • fastq files • optimal clustering • RNAseq • Spatial transcriptomics
ISBN-10	1-0716-2755-4 / 1071627554
ISBN-13	978-1-0716-2755-6 / 9781071627556
Zustand	Neuware