Statistical Analysis of Next Generation Sequencing Data

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical in...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Datta, Somnath (Editor ), Nettleton, Dan (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Frontiers in Probability and the Statistical Sciences,
Temas:
Biometry.
Medical genetics.
Cancer.
Biostatistics.
Medical Genetics.
Cancer Biology.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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
  • Functional PCA for differential expression testing with RNA-seq data
  • 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: A Model-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 Sequence Data from Paired Tumor-Normal Samples
  • Statistical Considerations in the Analysis of Rare Variants.

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