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.

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.