Transcriptome Data Analysis: Methods and Protocols

✍ Scribed by Yejun Wang,Ming-an Sun (eds.)

Publisher: Humana Press
Year: 2018
Tongue: English
Leaves: 239
Series: Methods in Molecular Biology 1751
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-x
Front Matter ....Pages 1-1
Comparison of Gene Expression Profiles in Nonmodel Eukaryotic Organisms with RNA-Seq (Han Cheng, Yejun Wang, Ming-an Sun)....Pages 3-16
Microarray Data Analysis for Transcriptome Profiling (Ming-an Sun, Xiaojian Shao, Yejun Wang)....Pages 17-33
Pathway and Network Analysis of Differentially Expressed Genes in Transcriptomes (Qianli Huang, Ming-an Sun, Ping Yan)....Pages 35-55
QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization (Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, Baohong Zhang)....Pages 57-70
Front Matter ....Pages 71-71
Tracking Alternatively Spliced Isoforms from Long Reads by SpliceHunter (Zheng Kuang, Stefan Canzar)....Pages 73-88
RNA-Seq-Based Transcript Structure Analysis with TrBorderExt (Yejun Wang, Ming-an Sun, Aaron P. White)....Pages 89-99
Analysis of RNA Editing Sites from RNA-Seq Data Using GIREMI (Qing Zhang)....Pages 101-108
Bioinformatic Analysis of MicroRNA Sequencing Data (Xiaonan Fu, Daoyuan Dong)....Pages 109-125
Microarray-Based MicroRNA Expression Data Analysis with Bioconductor (Emilio Mastriani, Rihong Zhai, Songling Zhu)....Pages 127-138
Identification and Expression Analysis of Long Intergenic Noncoding RNAs (Ming-an Sun, Rihong Zhai, Qing Zhang, Yejun Wang)....Pages 139-152
Analysis of RNA-Seq Data Using TEtranscripts (Ying Jin, Molly Hammell)....Pages 153-167
Front Matter ....Pages 169-169
Computational Analysis of RNA–Protein Interactions via Deep Sequencing (Lei Li, Konrad U. Förstner, Yanjie Chao)....Pages 171-182
Predicting Gene Expression Noise from Gene Expression Variations (Xiaojian Shao, Ming-an Sun)....Pages 183-198
A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data (Jinfeng Zou, Daoquan Xiang, Raju Datla, Edwin Wang)....Pages 199-208
Single-Cell Transcriptome Analysis Using SINCERA Pipeline (Minzhe Guo, Yan Xu)....Pages 209-222
Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues (Niya Wang, Lulu Chen, Yue Wang)....Pages 223-236
Back Matter ....Pages 237-238

✦ Subjects

Human Genetics

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