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Statistical genomics : methods and protocols / edited by Ewy Mathe, Sean Davis. -- New York : Humana Press, 2016. – (58.1481057/S797) |
Contents
PART I GROUNDWORK
1 Overview of Sequence Data Formats
2 Integrative Exploratory Analysis of Two or
More Genomic Datasets
3 Study Design for Sequencing Studies
4 Genomic Annotation Resources in
R/Bioconductor
PART
II PUBLIC GENOMIC DATA
5 The Gene Expression Omnibus Database
6 A Practical Guide to The Cancer Genome Atlas
(TCGA)
PART
III APPLICATIONS
7 Working with Oligonucleotide Arrays
8 Meta-Analysis in Gene Expression Studies
9 Practical Analysis of Genome Contact
Interaction Experiments
10 Quantitative Comparison of Large-Scale DNA
Enrichment Sequencing Data
11 Variant Calling From Next Generation Sequence
Data
12 Genome-Scale Analysis of Cell-Specific
Regulatory Codes Using Nuclear Enzymes
PART IV
Tools
13 NGS-QC Generator: A Quality Control System
for ChIP-Seq and Related Deep Sequencing-Generated Datasets
14 Operating on Genomic Ranges Using BEDOPS
15 GMAP and GSNAP for Genomic Sequence
Alignment: Enhancements to Speed, Accuracy, and Functionality
16 Visualizing Genomic Data Using Gviz and
Bioconductor
17 Introducing Machine Learning Concepts with
WEKA
18 Experimental Design and Power Calculation for
RNA-seq Experiments
19 It's DE-licious: A Recipe for Differential
Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in
edger
Index
