Description
Book SynopsisExome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinformatics. Computational Exome and Genome Analysis provides a practical introduction to all of the major areas in the field, enabling readers to develop a comprehensive understanding of the sequencing process and the entire computational analysis pipeline.
Trade Review"This book represents a timely contribution to the burgeoning field of exome and genome sequencing data analysis. It covers all pertinent topics ranging from raw data quality control to medical interpretation of genetic mutations, with detailed command line examples as well as in-depth explanations on every step of analysis. Highly recommended to any researchers, scientists, clinicians or students who are interested to learn practical skills on genome analysis."
-Kai Wang, Department of Biomedical Informatics, Columbia University
"This book provides a very comprehensive overview of all the fundamentals that are needed to work as a bioinformatician in the field of exome and genome analysis. All of the important processing steps are illustrated with practical examples and code. In addition, the casual writing style makes this book an easy read."
-Christian Gilissen, Department of Human Genetics, Radbound Univeristy Medical Center
"This book is an excellent example of a hybrid between a textbook and an up-to-date research reference on the latest bioinformatics tools available in this eld. Its rigorous and thorough approach makes it a reliable starting point for bioinformaticians and biologists. By including details on methodological aspects of some of the algorithms used for various components of the data analysis and coupling these with fully-commented examples and exercises, this book presents itself as a must-have for novices and experts alike. Given the fast pace of the field, no book can be exhaustive, however, the wide variety of tools presented here recommend it to a wide audience, both as expertise and focused research interests."
-Irina Ioana Mohorianu, Zentralblatt MATH
"This book represents a timely contribution to the burgeoning field of exome and genome sequencing data analysis. It covers all pertinent topics ranging from raw data quality control to medical interpretation of genetic mutations, with detailed command line examples as well as in-depth explanations on every step of analysis. Highly recommended to any researchers, scientists, clinicians or students who are interested to learn practical skills on genome analysis."
-Kai Wang, Department of Biomedical Informatics, Columbia University
"This book provides a very comprehensive overview of all the fundamentals that are needed to work as a bioinformatician in the field of exome and genome analysis. All of the important processing steps are illustrated with practical examples and code. In addition, the casual writing style makes this book an easy read."
-Christian Gilissen, Department of Human Genetics, Radbound Univeristy Medical Center
"This book is an excellent example of a hybrid between a textbook and an up-to-date research reference on the latest bioinformatics tools available in this eld. Its rigorous and thorough approach makes it a reliable starting point for bioinformaticians and biologists. By including details on methodological aspects of some of the algorithms used for various components of the data analysis and coupling these with fully-commented examples and exercises, this book presents itself as a must-have for novices and experts alike. Given the fast pace of the field, no book can be exhaustive, however, the wide variety of tools presented here recommend it to a wide audience, both as expertise and focused research interests."
-Irina Ioana Mohorianu, Zentralblatt MATH
Table of ContentsIntroduction. Whole Exome and Genome Sequencing. NGS Technology. Illumina Technology. Obtaining WES/WGS Data for this book. Raw Data Processing. FASTQ Format. Raw Data: Quality Control. Trimming. Alignment. Alignment: Mapping reads to the reference genome. SAM/BAM Format. Postprocessing the Alignment. Alignment Data: Quality control. Variant Calling. Variant Calling & Quality-based Filtering. Variant Call Format. Jannovar. Variant Annotation. Variant Calling: Quality Control. Integrative Genomics Viewer (IGV): Visualizing Alignments and Variants. De novo variants. Structural variation. Variant Filtering. Pedigree and Linkage Analysis. Intersection Analysis and Rare Variant Association Studies. Variant Frequency Analysis. Variant Pathogenicity Prediction. Prioritization. Variant Prioritization. Prioritization by Random Walk Analysis. Phenotype Analysis. Exomiser and Geniomiser. Medical Interpretation. Cancer. A (Very) Short Introduction to Cancer. Somantic variants in cancer. Tumor Evolution and Sample Purity. Driver Mutations and mutational signatures.
