Statistical Genomics

“This collection of articles offers a thorough overview of the field, making it an opportune and useful addition to the literature. The book is written in an accessible language and the variety of the topics which are presented recommends it as an excellent starting point or updated reference of the field. It is suitable for both post-graduate and established researchers, and the numerous examples that accompany the discussed topics recommend it as an asset.” (Irina Ioana Mohorianu, zbMATH 1346.92003, 2016)

• Overview of Sequence Data Formats.- Integrative Exploratory Analysis of Two or More Genomic Datasets.- Study Design for Sequencing Studies.- Genomic Annotation Resources in R/Bioconductor.- The Gene Expression Omnibus Database.- A Practical Guide to the Cancer Genome Atlas (TCGA).- Working with Oligonucleotide Arrays.- Meta-Analysis in Gene Expression Studies.- Practical Analysis of Genome Contact Interaction Experiments.- Quantitative Comparison of Large-Scale DNA Enrichment Sequencing Data.- Variant Calling From Next Generation Sequence Data.- Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes.- NGS-QC Generator: A Quality Control System for ChIP-seq and Related Deep Sequencing-Generated Datasets.- Operating on Genomic Ranges Using BEDOPS.- GMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality.- Visualizing Genomic Data using Gviz and Bioconductor.- Introducing Machine Learning Concepts with WEKA.- Experimental Design and Power Calculation for RNA-Seq Experiments.- It’s DE-licious: A Recipe for Differential Expression Analyses of RNA-Seq Experiments Using Quasi-Likelihood Methods in EdgeR.