Statistical Analysis of Next Generation Sequencing Data

Chapter 1 Statistical Analyses of Next Generation Sequencing Data: An Overview

Chapter 2 Using RNA-seq Data to Detect Differentially Expressed Genes

Chapter 3 Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR

Chapter 4 Analysis of Next Generation Sequencing Data Using Integrated Nested Laplace Approximation (INLA)

Chapter 5 Design of RNA Sequencing Experiments

Chapter 6 Measurement, Summary, and Methodological Variation in RNA-sequencing

Chapter 7 DE-FPCA: Testing Gene Differential Expression and Exon Usage Through Functional Principal Component Analysis

Chapter 8 Mapping of Expression Quantitative Trait Loci Using RNA-seq Data

Chapter 9 The Role of Spike-In Standards in the Normalization of RNA-seq

Chapter 10 Cluster Analysis of RNA-Sequencing Data

Chapter 11 Classification of RNA-seq Data

Chapter 12 Isoform Expression Analysis Based on RNA-seq Data

Chapter 13 RNA Isoform Discovery Through Goodness of Fit Diagnostics

Chapter 14 MOSAiCS-HMM: A Model-Based Approach for Detecting Regions of Histone Modifications from ChIP-Seq Data

Chapter 15 Hierarchical Bayesian Models for ChIP-seq Data

Chapter 16 Genotype Calling and Haplotype Phasing from Next Generation Sequencing Data

Chapter 17 Analysis of Metagenomic Data

Chapter 18 Detecting Copy Number Changes and Structural Rearrangements Using DNA Sequencing

Chapter 19 Statistical Methods for the Analysis of Next Generation Sequencing Data from Paired Tumor-Normal Samples

Chapter 20 Statistical Considerations in the Analysis of Rare Variants