Single Cell Transcriptomics : Methods and Protocols / edited by Raffaele A. Calogero, Vladimir Benes.

Format:

Book

Contributor:

Calogero, Raffaele A., Editor.

Beneš, Vladimír, Editor.

SpringerLink (Online service)

Series:

Springer Protocols (Springer-12345)

Methods in molecular biology 1940-6029 ; 2584

Methods in Molecular Biology, 1940-6029 ; 2584

Language:

English

Subjects (All):

Cytology.

Bioinformatics.

Cell Biology.

Local Subjects:

Cell Biology.

Bioinformatics.

Physical Description:

1 online resource (XI, 390 pages) : 126 illustrations, 121 illustrations in color.

Edition:

1st edition 2023.

Contained In:

Springer Nature eBook

Place of Publication:

New York, NY : Springer US : Imprint: Humana, 2023.

System Details:

text file PDF

Summary:

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.

Contents:

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 Associated To 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.

Other Format:

Printed edition:

ISBN:

978-1-0716-2756-3

9781071627563

Access Restriction:

Restricted for use by site license.