Overview
This volume details state-of-the-art computational methods designed to manage, analyze, and generally leverage epigenomic and epitranscriptomic data. Chapters guide readers through fine-mapping and quantification of modifications, visual analytics, imputation methods, supervised analysis, and integrative approaches for single-cell 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. Cutting-edge and thorough, Computational Epigenomics and Epitranscriptomics aims to provide an overview of epiomic protocols, making it easier for researchers to extract impactful biological insight from their data.
Full Product Details
Author: Pedro H. Oliveira
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 1st ed. 2023
Volume: 2624
Weight: 0.722kg
ISBN: 9781071629611
ISBN 10: 1071629611
Pages: 262
Publication Date: 02 February 2023
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand 
We will order this item for you from a manufactured on demand supplier.
Table of Contents
1. DNA methylation data analysis using Msuite Xiaojian Liu, Pengxiang Yuan, and Kun Sun 2. Interactive DNA methylation arrays analysis with ShinyÉPICo Octavio Morante-Palacios 3. Predicting Chromatin Interactions from DNA Sequence using DeepC Ron Schwessinger 4. Integrating single-cell methylome and transcriptome data with MAPLE Yasin Uzun, Hao Wu, and Kai Tan 5. Quantitative comparison of multiple chromatin immunoprecipitation-sequencing (ChIP-seq) experiments with spikChIP Enrique Blanco, Cecilia Ballaré, Luciano Di Croce, and Sergi Aranda 6. A Guide To MethylationToActivity: A Deep-Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes In Individual Tumors Karissa Dieseldorff Jones, Daniel Putnam, Justin Williams, and Xiang Chen 7. DNA modification patterns filtering and analysis using DNAModAnnot Alexis Hardy, Sandra Duharcourt, and Matthieu Defrance 8. Methylome imputation by methylation patterns Ya-Ting Chang, Ming-Ren Yen, and Pao-Yang Chen 9. Sequoia: a framework for visual analysis of RNA modifications from direct RNA sequencing data Ratanond Koonchanok, Swapna Vidhur Daulatabad, Khairi Reda, and Sarath Chandra Janga 10. Predicting pseudouridine sites with Porpoise Xudong Guo, Fuyi Li, and Jiangning Song 11. Pseudouridine Identification and Functional Annotation with PIANO Jiahui Yao, Cuiyueyue Hao, Kunqi Chen, Jia Meng, and Bowen Song 12. Analyzing mRNA epigenetic sequencing data with TRESS Zhenxing Guo, Andrew M. Shafik, Peng Jin, Zhijin Wu, and Hao Wu 13. Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores Luca Cozzuto, Anna Delgado-Tejedor, Toni Hermoso Pulido, Eva Maria Novoa, and Julia Ponomarenko 14. Data Analysis Pipeline for Detection and Quantification of Pseudouridine (ψ) in RNA by HydraPsiSeq Florian Pichot, Virginie Marchand, Mark Helm, and Yuri Motorin 15. Analysis of RNA sequences and modifications using NASE Samuel Wein 16. Mapping of RNA modifications by direct Nanopore sequencing and JACUSA2 Amina Lemsara, Christoph Dieterich, and Isabel Naarmann-de Vries
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