Computational Methods for Single-Cell Data Analysis

✍ Scribed by Guo-Cheng Yuan

• Publisher: Humana Press
• Year: 2019
• Tongue: English
• Leaves: 270
• Edition: Hardcover
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-x
Quality Control of Single-Cell RNA-seq (Peng Jiang)....Pages 1-9
Normalization for Single-Cell RNA-Seq Data Analysis (Rhonda Bacher)....Pages 11-23
Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing (Beomseok Kim, Eunmin Lee, Jong Kyoung Kim)....Pages 25-43
Identification of Cell Types from Single-Cell Transcriptomic Data (Karthik Shekhar, Vilas Menon)....Pages 45-77
Rare Cell Type Detection (Lan Jiang)....Pages 79-89
scMCA: A Tool to Define Mouse Cell Types Based on Single-Cell Digital Expression (Huiyu Sun, Yincong Zhou, Lijiang Fei, Haide Chen, Guoji Guo)....Pages 91-96
Differential Pathway Analysis (Jean Fan)....Pages 97-114
Pseudotime Reconstruction Using TSCAN (Zhicheng Ji, Hongkai Ji)....Pages 115-124
Estimating Differentiation Potency of Single Cells Using Single-Cell Entropy (SCENT) (Weiyan Chen, Andrew E. Teschendorff)....Pages 125-139
Inference of Gene Co-expression Networks from Single-Cell RNA-Sequencing Data (Alicia T. Lamere, Jun Li)....Pages 141-153
Single-Cell Allele-Specific Gene Expression Analysis (Meichen Dong, Yuchao Jiang)....Pages 155-174
Using BRIE to Detect and Analyze Splicing Isoforms in scRNA-Seq Data (Yuanhua Huang, Guido Sanguinetti)....Pages 175-185
Preprocessing and Computational Analysis of Single-Cell Epigenomic Datasets (Caleb Lareau, Divy Kangeyan, Martin J. Aryee)....Pages 187-202
Experimental and Computational Approaches for Single-Cell Enhancer Perturbation Assay (Shiqi Xie, Gary C. Hon)....Pages 203-221
Antigen Receptor Sequence Reconstruction and Clonality Inference from scRNA-Seq Data (Ida Lindeman, Michael J. T. Stubbington)....Pages 223-249
A Hidden Markov Random Field Model for Detecting Domain Organizations from Spatial Transcriptomic Data (Qian Zhu)....Pages 251-268
Back Matter ....Pages 269-271