Literature DB >> 35980574

Analysis of Single-Cell Transcriptome Data in Drosophila.

Schayan Yousefian1,2,3, Maria Jelena Musillo4, Josephine Bageritz5.   

Abstract

The fly Drosophila is a versatile model organism that has led to fascinating biological discoveries. In the past few years, Drosophila researchers have used single-cell RNA-sequencing (scRNA-seq) to gain insights into the cellular composition, and developmental processes of various tissues and organs. Given the success of single-cell technologies a variety of computational tools and software packages were developed to enable and facilitate the analysis of scRNA-seq data. In this book chapter we want to give guidance on analyzing droplet-based scRNA-seq data from Drosophila. We will initially describe the preprocessing commonly done for Drosophila, point out possible downstream analyses, and finally highlight computational methods developed using Drosophila scRNA-seq data.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Computational methods; Data analysis; Droplet based; Drosophila; Seurat; Single-cell RNA-seq; Software packages

Mesh:

Year:  2022        PMID: 35980574     DOI: 10.1007/978-1-0716-2541-5_4

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  76 in total

1.  Smart-seq2 for sensitive full-length transcriptome profiling in single cells.

Authors:  Simone Picelli; Åsa K Björklund; Omid R Faridani; Sven Sagasser; Gösta Winberg; Rickard Sandberg
Journal:  Nat Methods       Date:  2013-09-22       Impact factor: 28.547

2.  Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

Authors:  Allon M Klein; Linas Mazutis; Ilke Akartuna; Naren Tallapragada; Adrian Veres; Victor Li; Leonid Peshkin; David A Weitz; Marc W Kirschner
Journal:  Cell       Date:  2015-05-21       Impact factor: 41.582

3.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

Authors:  Evan Z Macosko; Anindita Basu; Rahul Satija; James Nemesh; Karthik Shekhar; Melissa Goldman; Itay Tirosh; Allison R Bialas; Nolan Kamitaki; Emily M Martersteck; John J Trombetta; David A Weitz; Joshua R Sanes; Alex K Shalek; Aviv Regev; Steven A McCarroll
Journal:  Cell       Date:  2015-05-21       Impact factor: 41.582

4.  Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding.

Authors:  Alexander B Rosenberg; Charles M Roco; Richard A Muscat; Anna Kuchina; Paul Sample; Zizhen Yao; Lucas T Graybuck; David J Peeler; Sumit Mukherjee; Wei Chen; Suzie H Pun; Drew L Sellers; Bosiljka Tasic; Georg Seelig
Journal:  Science       Date:  2018-03-15       Impact factor: 47.728

5.  mRNA-Seq whole-transcriptome analysis of a single cell.

Authors:  Fuchou Tang; Catalin Barbacioru; Yangzhou Wang; Ellen Nordman; Clarence Lee; Nanlan Xu; Xiaohui Wang; John Bodeau; Brian B Tuch; Asim Siddiqui; Kaiqin Lao; M Azim Surani
Journal:  Nat Methods       Date:  2009-04-06       Impact factor: 28.547

6.  Highly multiplexed and strand-specific single-cell RNA 5' end sequencing.

Authors:  Saiful Islam; Una Kjällquist; Annalena Moliner; Pawel Zajac; Jian-Bing Fan; Peter Lönnerberg; Sten Linnarsson
Journal:  Nat Protoc       Date:  2012-04-05       Impact factor: 13.491

7.  Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.

Authors:  Daniel Ramsköld; Shujun Luo; Yu-Chieh Wang; Robin Li; Qiaolin Deng; Omid R Faridani; Gregory A Daniels; Irina Khrebtukova; Jeanne F Loring; Louise C Laurent; Gary P Schroth; Rickard Sandberg
Journal:  Nat Biotechnol       Date:  2012-08       Impact factor: 54.908

8.  Massively parallel digital transcriptional profiling of single cells.

Authors:  Grace X Y Zheng; Jessica M Terry; Phillip Belgrader; Paul Ryvkin; Zachary W Bent; Ryan Wilson; Solongo B Ziraldo; Tobias D Wheeler; Geoff P McDermott; Junjie Zhu; Mark T Gregory; Joe Shuga; Luz Montesclaros; Jason G Underwood; Donald A Masquelier; Stefanie Y Nishimura; Michael Schnall-Levin; Paul W Wyatt; Christopher M Hindson; Rajiv Bharadwaj; Alexander Wong; Kevin D Ness; Lan W Beppu; H Joachim Deeg; Christopher McFarland; Keith R Loeb; William J Valente; Nolan G Ericson; Emily A Stevens; Jerald P Radich; Tarjei S Mikkelsen; Benjamin J Hindson; Jason H Bielas
Journal:  Nat Commun       Date:  2017-01-16       Impact factor: 14.919

Review 9.  Single-Cell RNA-Seq Technologies and Related Computational Data Analysis.

Authors:  Geng Chen; Baitang Ning; Tieliu Shi
Journal:  Front Genet       Date:  2019-04-05       Impact factor: 4.599

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