Computational epigenomics and epitranscriptomics / edited by Pedro H. Oliveira. -- New York, NY : Humana Press, 2023. – (58.17/M592/v.2624)

Contents

Preface
Contributors
1  DNA Methylation Data Analysis Using Msuite
2  Interactive DNA Methylation Array Analysis with ShinyEPICo
3  Predicting Chromatin Interactions from DNA Sequence Using DeepC
4  Integrating Single-Cell Methylome and Transcriptome Data with MAPLE
5  Quantitative Comparison of Multiple Chromatin Immunoprecipitation-Sequencing (ChIP-seq) Experiments with spikChIP
6  A Guide to Methylation To Activity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors
7  DNA Modification Patterns Filtering and Analysis Using DNAModAnnot
8  Methylome Imputation by Methylation Patterns
9  Sequoia: A Framework for Visual Analysis of RNA Modifications from Direct RNA Sequencing Data
10  Predicting Pseudouridine Sites with Porpoise
11  Pseudouridine Identification and Functional Annotation with PIANO
12  Analyzing mRNA Epigenetic Sequencing Data with TRESS
13  Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores
14  Data Analysis Pipeline for Detection and Quantification of Pseudouridine (~,) in RNA by HydraPsiSeq
15  Analysis of RNA Sequences and Modifications Using NASE
16  Mapping of RNA Modifications by Direct Nanopore Sequencing and JACUSA2
Index