This volume provides practical guidance on a variety of techniques and steps to ensure successful variant calling. Chapters detail methods for variant calling from single-nucleotide variants to structural variants, variant calling in specialized data types such as RNA-seq and UMI-tagged sequencing, alignment-free genotyping and SNP calling, variant detection in single-cell DNA sequencing data, variant annotation, and preanalytical quality control to ensure successful variant calling. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists step-by-step protocol to execute the algorithms, describes the input and output data, and includes tips on troubleshooting and known pitfalls. Authoritative and cutting-edge, Variant Calling: Methods and Protocols aims to be a foundation for future studies and to be a source of inspiration for new investigations in the field.

Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesâ??or over 50 million gigabytesâ??of genomic data, and theyâ??re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian Oâ??Connor of the UC Santa Cruz Genomics Institute, guide you through the process. Youâ??ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra

The 14 contributed chapters in this book survey the most recent developments in high-performance algorithms for NGS data, offering fundamental insights and technical information specifically on indexing, compression and storage; error correction; alignment; and assembly. The book will be of value to researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences.

Benson Fisher thought that a scholarship to Maxfield Academy would be the ticket out of his dead-end life. He was wrong. Now he’s trapped in a school that’s surrounded by a razor-wire fence. A school where video cameras monitor his every move. Where there are no adults. Where the kids have split into groups in order to survive. Where breaking the rules equals death. But when Benson stumbles upon the school’s real secret, he realizes that playing by the rules could spell a fate worse than death, and that escape—his only real hope for survival—may be impossible.

This book offers comprehensive information on the genomics of spruces (Picea spp.), naturally abundant conifer tree species that are widely distributed in the Northern Hemisphere. Due to their tremendous ecological and economic importance, the management of forest genetic resources has chiefly focused on conservation and tree improvement. A draft genome sequence of the 20-gigabase Norway spruce genome was published in the journal Nature in 2013. Continuous efforts to improve the spruce genome assembly are underway, but are hindered by the inherent characteristics of conifer genomes: high amounts of repetitive sequences (introns and transposable elements) in the genome and large gene family expansions with regards to abiotic stress, secondary metabolism and spruces' defense responses to pathogens and herbivory. This book presents the latest information on the status of genome assemblies, provides detailed insights into transposable elements and methylation patterns, and highlights the extensive genomic resources available for inferring population genomics and climate adaptation, as well as emerging genomics tools for tree improvement programs. In addition, this volume features whole-genome comparisons among conifer species, and demonstrates how functional genomics can be used to improve gene function annotations. The book closes with an outlook on emerging fields of research in spruce genomics.

Exome 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.

Recent advances in plant genomics and molecular biology have revolutionized our understanding of plant genetics, providing new opportunities for more efficient and controllable plant breeding. Successful techniques require a solid understanding of the underlying molecular biology as well as experience in applied plant breeding. Bridging the gap between developments in biotechnology and its applications in plant improvement, Molecular Plant Breeding provides an integrative overview of issues from basic theories to their applications to crop improvement including molecular marker technology, gene mapping, genetic transformation, quantitative genetics, and breeding methodology.

Guided by standard bioscience workflows in high-throughput sequencing analysis, this book for graduate students, researchers, and professionals in bioinformatics and computer science offers a unified presentation of genome-scale algorithms. This new edition covers the use of minimizers and other advanced data structures in pangenomics approaches.

Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Virus bioinformatics is evolving and succeeding as an area of research in its own right, representing the interface of virology and computer science. Bioinformatic approaches to investigate viral infections and outbreaks have become central to virology research, and have been successfully used to detect, control, and treat infections of humans and animals. As part of the Third Annual Meeting of the European Virus Bioinformatics Center (EVBC), we have published this Special Issue on Virus Bioinformatics.