Datta S., Nettleton D. (Eds.) Statistical Analysis of Next Generation Sequencing Data

N.-Y.: Springer, 2014. - 438p.Statistical Analyses of Next Generation Sequencing Data:
An Overview
Using RNA-seq Data to Detect Differentially Expressed Genes
Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR
Analysis of Next Generation Sequencing Data Using Integrated Nested Laplace Approximation (INLA)
Design of RNA Sequencing Experiments
Measurement, Summary, and Methodological Variation in RNA-sequencing
DE-FPCA: Testing Gene Differential Expression and Exon Usage Through Functional Principal Component Analysis
Mapping of Expression Quantitative Trait Loci Using RNA-seq Data
The Role of Spike-In Standards in the Normalization of RNA-seq
Cluster Analysis of RNA-Sequencing Data.
Classification of RNA-seq Data
Isoform Expression Analysis Based on RNA-seq Data
RNA Isoform Discovery Through Goodness of Fit Diagnostics
MOSAiCS-HMM: AModel-Based Approach for Detecting Regions of Histone Modifications from ChIP-Seq Data
Hierarchical Bayesian Models for ChIP-seq Data
Genotype Calling and Haplotype Phasing from Next Generation Sequencing Data
Analysis of Metagenomic Data
Detecting Copy Number Changes and Structural Rearrangements Using DNA Sequencing
Statistical Methods for the Analysis of Next Generation Sequencing Data from Paired Tumor-Normal Samples
Statistical Considerations in the Analysis of Rare Variants