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Computational Methods for Single-Cell Data Analysis

  • Guo-Cheng Yuan
Book

Part of the Methods in Molecular Biology book series (MIMB, volume 1935)

Table of contents

  1. Front Matter
    Pages i-x
  2. Beomseok Kim, Eunmin Lee, Jong Kyoung Kim
    Pages 25-43
  3. Lan Jiang
    Pages 79-89
  4. Huiyu Sun, Yincong Zhou, Lijiang Fei, Haide Chen, Guoji Guo
    Pages 91-96
  5. Jean Fan
    Pages 97-114
  6. Zhicheng Ji, Hongkai Ji
    Pages 115-124
  7. Meichen Dong, Yuchao Jiang
    Pages 155-174
  8. Yuanhua Huang, Guido Sanguinetti
    Pages 175-185
  9. Caleb Lareau, Divy Kangeyan, Martin J. Aryee
    Pages 187-202
  10. Ida Lindeman, Michael J. T. Stubbington
    Pages 223-249
  11. Back Matter
    Pages 269-271

About this book

Introduction

This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. 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.

Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.

Keywords

Experimental data Cellular heterogeneity Computational methods Spatial transcriptomics Sequencing Rare cell-type identification

Editors and affiliations

  • Guo-Cheng Yuan
    • 1
  1. 1.Dana–Farber Cancer Institute and Harvard Chan, School of Public HealthBostonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-9057-3
  • Copyright Information Springer Science+Business Media, LLC, part of Springer Nature 2019
  • Publisher Name Humana Press, New York, NY
  • eBook Packages Springer Protocols
  • Print ISBN 978-1-4939-9056-6
  • Online ISBN 978-1-4939-9057-3
  • Series Print ISSN 1064-3745
  • Series Online ISSN 1940-6029
  • Buy this book on publisher's site