Computational Exome and Genome Analysis

Peter Robinson is Professor for Medical Genomics at the Charité Universitätsmedizin Berlin, and professor for Bioinformatics at the Free University of Berlin. He studied Mathematics and Computer Science at Columbia University as well as Medicine at the University of Pennsylvania. Peter has led a bioinformatics research group since 2004. He has led the development of the Human Phenotype Ontology, which is used internationally to describe the clinical manifestations of patients with genetic disorders and to empower exome and genome analysis. His group has published algorithms for exome, genome, ChIP-seq and NGS T Cell Receptor profiling. Rosario M. Piro is an Assistant Professor of Bioinformatics at Freie Universität Berlin and Charité-Universitätsmedizin Berlin, Germany. His research is mainly focused on computational neuropathology, including cancer genetics/genomics of brain tumors as well as network analysis and disease gene prediction for neurological disorders; and computational oncology in general, including the development and evolution of cancers in other organs or tissues. His expertise in next-generation sequencing data analysis techniques is complemented by a past research experience in the field of data-intensive distributed computing.Marten Jäger is a graduate student in Peter Robinson’s group and has developed pipelines for exome and genome sequencing data. Marten’s work has involved the development of algorithms for variant annotation, exome prioritization, RNA-seq, and integrative genomics analysis.

"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

• Introduction. 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.