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  High-Throughput Single-Cell RNA Sequencing and Data Analaysis

Sagar, S., Hermann, J. S., Pospisilik, J. A., & Grün, D. (2018). High-Throughput Single-Cell RNA Sequencing and Data Analaysis. Methods in Molecular Biology, 1766, 257-283. doi:10.1007/978-1-4939-7768-0_15.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-64C0-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-EB02-1
Genre: Journal Article

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 Creators:
Sagar, Sagar1, Author
Hermann, Josip Stefan1, Author
Pospisilik, John Andrew1, Author
Grün, Dominic, Author              
Affiliations:
1Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, 79108 Freiburg, DE, ou_2243640              

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Free keywords: Single cell RNA sequencing, High-throughput, Single cell data analysis, CEL-Seq2, Next-generation sequencing
 Abstract: Understanding biological systems at a single cell resolution may reveal several novel insights which remain masked by the conventional population-based techniques providing an average readout of the behavior of cells. Single-cell transcriptome sequencing holds the potential to identify novel cell types and characterize the cellular composition of any organ or tissue in health and disease. Here, we describe a customized high-throughput protocol for single-cell RNA-sequencing (scRNA-seq) combining flow cytometry and a nanoliter-scale robotic system. Since scRNA-seq requires amplification of a low amount of endogenous cellular RNA, leading to substantial technical noise in the dataset, downstream data filtering and analysis require special care. Therefore, we also briefly describe in-house state-of-the-art data analysis algorithms developed to identify cellular subpopulations including rare cell types as well as to derive lineage trees by ordering the identified subpopulations of cells along the inferred differentiation trajectories.

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Language(s): eng - English
 Dates: 2018
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/978-1-4939-7768-0_15
 Degree: -

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Title: Methods in Molecular Biology
  Other : Methods Mol. Biol.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Clifton, N.J. : Humana Press
Pages: - Volume / Issue: 1766 Sequence Number: - Start / End Page: 257 - 283 Identifier: ISSN: 1064-3745
CoNE: https://pure.mpg.de/cone/journals/resource/954927725544