Transcriptome data analysis : methods and protocols
著者
書誌事項
Transcriptome data analysis : methods and protocols
（Methods in molecular biology / John M. Walker, series editor, 1751）（Springer protocols）
Humana Press, c2018
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内容説明・目次
内容説明
This detailed volume provides comprehensive practical guidance on transcriptome data analysis for a variety of scientific purposes. Beginning with general protocols, the collection moves on to explore protocols for gene characterization analysis with RNA-seq data as well as protocols on several new applications of transcriptome studies. Written for the highly successful Methods in Molecular Biology series, 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 useful, Transcriptome Data Analysis: Methods and Protocols serves as an ideal guide to the expanding purposes of this field of study.
目次
Part I: General Protocols on Transcriptome Data Analysis
1. Comparison of Gene Expression Profiles in Non-Model Eukaryotic Organisms with RNA-Seq
Han Cheng, Yejun Wang, and Ming-an Sun
2. Microarray Data Analysis for Transcriptome Profiling
Ming-an Sun, Xiaojian Shao, and Yejun Wang
3. Pathway and Network Analysis of Differentially Expressed Genes in Transcriptomes
Qianli Huang, Ming-an Sun, and Ping Yan
4. QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, and Baohong Zhang
Part II: Objective-Specialized Transcriptome Data Analysis
5. Tracking Alternatively Spliced Isoforms from Long Reads by SpliceHunter
Zheng Kuang and Stefan Canzar
6. RNA-Seq-Based Transcript Structure Analysis with TrBorderExt
Yejun Wang, Ming-an Sun, and Aaron P. White
7. Analysis of RNA Editing Sites from RNA-Seq Data Using GIREMI
Qing Zhang
8. Bioinformatic Analysis of MicroRNA Sequencing Data
Xiaonan Fu and Daoyuan Dong
9. Microarray-Based MicroRNA Expression Data Analysis with Bioconductor
Emilio Mastriani, Rihong Zhai, and Songling Zhu
10. Identification and Expression Analysis of Long Intergenic Non-Coding RNAs
Ming-an Sun, Rihong Zhai, Qing Zhang, and Yejun Wang
11. Analysis of RNA-Seq Data Using TEtranscripts
Ying Jin and Molly Hammell
Part III: New Applications of Transcriptome
12. Computational Analysis of RNA-Protein Interactions via Deep Sequencing
Lei Li, Konrad U. Foerstner, and Yanjie Chao
13. Predicting Gene Expression Noise from Gene Expression Variations
Xiaojian Shao and Ming-an Sun
14. A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data
Jinfeng Zou, Daoquan Xiang, Raju Datla, and Edwin Wang
15. Single-Cell Transcriptome Analysis Using SINCERA Pipeline
Minzhe Guo and Yan Xu
16. Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues
Niya Wang, Lulu Chen, and Yue Wang
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