Full-Length Single-Cell RNA Sequencing with Smart-seq2
| Autor: | Simone Picelli |
|---|---|
| Přispěvatelé: | Proserpio, Valentina |
| Rok vydání: | 2019 |
| Předmět: |
methods [High-Throughput Nucleotide Sequencing]
Computer science Cell metabolism [Transposases] RNA-Seq Computational biology metabolism [DNA Complementary] Set (abstract data type) 03 medical and health sciences 0302 clinical medicine ddc:570 Gene expression medicine Animals Humans genetics [RNA] Sensitivity (control systems) Throughput (business) Gene Library 030304 developmental biology methods [Single-Cell Analysis] 0303 health sciences RNA Reverse Transcription Gold standard (test) genetics [DNA Complementary] medicine.anatomical_structure Transcriptome 030217 neurology & neurosurgery methods [Gene Expression Profiling] |
| Zdroj: | Methods in Molecular Biology ISBN: 9781493992393 New York, NY : Springer New York, Methods in Molecular Biology 1979, 25-44 (2019). doi:10.1007/978-1-4939-9240-9_3 Single Cell Methods / Proserpio, Valentina (Editor) ; New York, NY : Springer New York, 2019, Chapter 3 ; ISSN: 1064-3745=1940-6029 ; ISBN: 978-1-4939-9239-3=978-1-4939-9240-9 ; doi:10.1007/978-1-4939-9240-9 |
| DOI: | 10.1007/978-1-4939-9240-9_3 |
| Popis: | In the last few years single-cell RNA sequencing (scRNA-seq) has enabled the investigation of cellular heterogeneity at the transcriptional level, the characterization of rare cell types as well as the detailed analysis of the stochastic nature of gene expression. A large number of methods have been developed, varying in their throughput, sensitivity, and scalability. A major distinction is whether they profile only 5'- or 3'-terminal part of the transcripts or allow for the characterization of the entire length of the transcripts. Among the latter, Smart-seq2 is still considered the "gold standard" due to its sensitivity, precision, lower cost, scalability and for being easy to set up on automated platforms. In this chapter I describe how to efficiently generate sequencing-ready libraries, highlight common issues and pitfalls, and offer solutions for generating high-quality data. |
| Databáze: | OpenAIRE |
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