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Complex Genome Analysis With High Throughput Sequencing Data
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Book Synopsis Complex Genome Analysis with High-throughput Sequencing Data by : Xin Li
Download or read book Complex Genome Analysis with High-throughput Sequencing Data written by Xin Li and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The genomes of most eukaryotes are large and complex. The presence of large amounts of non-coding sequences is a general property of the genomes of complex eukaryotes. High-throughput sequencing is increasingly important for the study of complex genomes. In this dissertation, we focus on two computational problems for high-throughput sequence data analysis, including detecting circular RNA and calling structural variations (especially deletions). Circular RNA (or circRNA) is a kind of non-coding RNA, which consists of a circular configuration through a typical 5' to 3' phosphodiester bond by non-canonical splicing. CircRNA was originally thought as the byproduct from the process of mis-splicing and considered to be of low abundance. Recently, however, circRNA is considered as a new class of functional molecule, and the importance of circRNA in gene regulation and their biological functions in some human diseases have started to be recognized. In this research work, we propose two algorithms to detect potential circRNA. In order to improve the performance of running time, we design an algorithm called CircMarker to find circRNA by creating k-mer table rather than conventional reads mapping. Furthermore, we develop an algorithm named CircDBG by taking advantage of the information from both reads and annotated genome to create de Bruijn graph for circRNA detection, which improves the accuracy and sensitivity. Structural variation (SV), which ranges from 50 bp to ~3 Mb in size, is an important type of genetic variations. Deletion is a type of SV in which a part of a chromosome or a sequence of DNA is lost during DNA replication. In this research work, we develop a new method called EigenDel for detecting genomic deletions. EigenDel first takes advantage of discordant read-pairs and clipped reads to get initial deletion candidates. Then, EigenDel clusters similar deletion candidates together and calls true deletions from each cluster by using unsupervised learning method. EigenDel outperforms other major methods in terms of balancing accuracy and sensitivity as well as reducing bias. Our results in this dissertation show that sequencing data can be used to study complex genomes by using effective computational approaches.
Book Synopsis Statistical Analysis of Next Generation Sequencing Data by : Somnath Datta
Download or read book Statistical Analysis of Next Generation Sequencing Data written by Somnath Datta and published by Springer. This book was released on 2014-07-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.
Book Synopsis Genome Analysis and Human Health by : Leena Rawal
Download or read book Genome Analysis and Human Health written by Leena Rawal and published by Springer. This book was released on 2017-06-08 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights selected current data and its relevance in the human health care system, offering a fundamental primer on genetics and human health. With the advent of new high-throughput technologies (for the whole genome including exome sequencing), the conventional focus on genetics and individual genes is now shifting toward the analysis of complex genes, gene-gene interactions and the association between genes and environment, including epigenetics. The rapidly changing scientific research landscape, with the ever-growing influx of data on one hand and emergence of newer and more complicated diseases on the other, has created a dilemma for researchers and caregivers, who are still hopeful that advances in genetics and genomics will provide avenues for the understanding, prevention and possible cure of human diseases. The book focuses on the interactions between genes and proteins at both the transcriptome and proteome levels, which in turn affect the human genome and health. Additionally, it covers the domain that must be explored in order to understand the gene-gene and protein-protein interactions that contribute to human health. The book offers a valuable guide for all students and researchers working in the area of molecular genetics and genomics.
Book Synopsis Genetic Analysis of Complex Disease by : William K. Scott
Download or read book Genetic Analysis of Complex Disease written by William K. Scott and published by John Wiley & Sons. This book was released on 2021-11-11 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Analysis of Complex Diseases An up-to-date and complete treatment of the strategies, designs and analysis methods for studying complex genetic disease in human beings In the newly revised Third Edition of Genetic Analysis of Complex Diseases, a team of distinguished geneticists delivers a comprehensive introduction to the most relevant strategies, designs and methods of analysis for the study of complex genetic disease in humans. The book focuses on concepts and designs, thereby offering readers a broad understanding of common problems and solutions in the field based on successful applications in the design and execution of genetic studies. This edited volume contains contributions from some of the leading voices in the area and presents new chapters on high-throughput genomic sequencing, copy-number variant analysis and epigenetic studies. Providing clear and easily referenced overviews of the considerations involved in genetic analysis of complex human genetic disease, including sampling, design, data collection, linkage and association studies and social, legal and ethical issues. Genetic Analysis of Complex Diseases also provides: A thorough introduction to study design for the identification of genes in complex traits Comprehensive explorations of basic concepts in genetics, disease phenotype definition and the determination of the genetic components of disease Practical discussions of modern bioinformatics tools for analysis of genetic data Reflecting on responsible conduct of research in genetic studies, as well as linkage analysis and data management New expanded chapter on complex genetic interactions This latest edition of Genetic Analysis of Complex Diseases is a must-read resource for molecular biologists, human geneticists, genetic epidemiologists and pharmaceutical researchers. It is also invaluable for graduate students taking courses in statistical genetics or genetic epidemiology.
Book Synopsis Beginners Guide To Bioinformatics For High Throughput Sequencing by : Tan Tin Wee
Download or read book Beginners Guide To Bioinformatics For High Throughput Sequencing written by Tan Tin Wee and published by World Scientific. This book was released on 2018-10-05 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologists find computing bewildering; yet they are expected to be able to process the voluminous data available from the machines they buy and the datasets that has accumulated in genomic databanks worldwide. It is now increasingly difficult for them to avoid dealing with large volumes of data, that goes beyond just doing manual programming.Most books in this realm are full of equations and complex code but this book gives a much gentler entry point particularly for biologists, with code snippets users can use to cut and paste, and run on their Linux or MacOSX operating system or cloud instance. It also provides a step by step installation instructions which they can easily follow. Those who are in the field of genome sequencing and already familiar with the procedures of analysis, may also find this book useful in closing some knowledge gaps.High throughput sequencing requires high throughput and high performance computing. This book provides a gentle entry to high throughput sequencing by dealing with simple skills which the average biologist is increasingly required to master. You will find this book a breeze to read, and some suggestions in this book maybe new to you, something you might want to try out.
Book Synopsis Toward a More Accurate Genome by : William Jacob Benhardt Biesinger
Download or read book Toward a More Accurate Genome written by William Jacob Benhardt Biesinger and published by . This book was released on 2014 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-throughput sequencing enables basic and translational biology to query the mechanics of both life and disease at single-nucleotide resolution and with breadth that spans the genome. This revolutionary technology is a major tool in biomedical research, impacting our understanding of life's most basic mechanics and affecting human health and medicine. Unfortunately, this important technology produces very large, error-prone datasets that require substantial computational processing before experimental conclusions can be made. Since errors and hidden biases in the data may influence empirically-derived conclusions, accurate algorithms and models of the data are critical. This thesis focuses on the development of statistical models for high-throughput sequencing data which are capable of handling errors and which are built to reflect biological realities. First, we focus on increasing the fraction of the genome that can be reliably queried in biological experiments using high-throughput sequencing methods by expanding analysis into repeat regions of the genome. The method allows partial observation of the gene regulatory network topology through identification of transcription factor binding sites using Chromatin Immunoprecipitation followed by high-throughput sequencing (ChIP-seq). Binding site clustering, or "peak-calling", can be frustrated by the complex, repetitive nature of genomes. Traditionally, these regions are censored from any interpretation, but we re-enable their interpretation using a probabilistic method for realigning problematic DNA reads. Second, we leverage high-throughput sequencing data for the empirical discovery of underlying epigenetic cell state, enabled through analysis of combinations of histone marks. We use a novel probabilistic model to perform spatial and temporal clustering of histone marks and capture mark combinations that correlate well with cell activity. A first in epigenetic modeling with high-throughput sequencing data, we not only pool information across cell types, but directly model the relationship between them, improving predictive power across several datasets. Third, we develop a scalable approach to genome assembly using high-throughput sequencing reads. While several assembly solutions exist, most don't scale well to large datasets, requiring computers with copious memory to assemble large genomes. Throughput continues to increase and the large datasets available today and in the near future will require truly scalable methods. We present a promising distributed method for genome assembly which distributes the de Bruijn graph across many computers and seamlessly spills to disk when main memory is insufficient. We also show novel graph cleaning algorithms which should handle increased errors from large datasets better than traditional graph structure-based cleaning. High-throughput sequencing plays an important role in biomedical research, and has already affected human health and medicine. Future experimental procedures will continue to rely on statistical methods to provide crucial error and bias correction, in addition to modeling expected outcomes. Thus, further development of robust statistical models is critical to the future high-throughput sequencing, ensuring a strong foundation for correct biological conclusions.
Book Synopsis Bioinformatics, Supercomputing And Complex Genome Analysis - Proceedings Of The 2nd International Conference by : Hwa A Lim
Download or read book Bioinformatics, Supercomputing And Complex Genome Analysis - Proceedings Of The 2nd International Conference written by Hwa A Lim and published by World Scientific. This book was released on 1993-09-07 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the beginning of the genome project, the necessary involvement of scientists of widely divergent backgrounds has been evident. The proper handling, analysis, dissemination of information, and the control and data gathering of automated process are areas where computers are directly involved. Thus computers are intimately tied into the production and analysis of biological data. However, many challenges lie ahead.This volume is a collection of selected oral and poster presentations given at The Second International Conference on Bioinformatics, Supercomputing and Complex Genome Analysis, organized to address some of these challenges. The topics include the current status and future prospects of genome map, mapping and sequencing, complex genome analysis,linguistic and neural network approaches, database issues, and computer tools in the genome project. The volume will be ideal for students, newcomers, young researchers and experts alike, who are computationally or experimentally oriented.Keynote Speakers: C L Smith, D Grothues, T Ito, T Sano, D Wang, Y-W Zhu, C R Canton & R J Rohins.
Book Synopsis Statistical Methods for the Analysis of Genomic Data by : Hui Jiang
Download or read book Statistical Methods for the Analysis of Genomic Data written by Hui Jiang and published by MDPI. This book was released on 2020-12-29 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.
Book Synopsis Evolution of Translational Omics by : Institute of Medicine
Download or read book Evolution of Translational Omics written by Institute of Medicine and published by National Academies Press. This book was released on 2012-09-13 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.
Book Synopsis Advances in Bioinformatics by : Vijai Singh
Download or read book Advances in Bioinformatics written by Vijai Singh and published by Springer Nature. This book was released on 2021-07-31 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest developments in bioinformatics, highlighting the importance of bioinformatics in genomics, transcriptomics, metabolism and cheminformatics analysis, as well as in drug discovery and development. It covers tools, data mining and analysis, protein analysis, computational vaccine, and drug design. Covering cheminformatics, computational evolutionary biology and the role of next-generation sequencing and neural network analysis, it also discusses the use of bioinformatics tools in the development of precision medicine. This book offers a valuable source of information for not only beginners in bioinformatics, but also for students, researchers, scientists, clinicians, practitioners, policymakers, and stakeholders who are interested in harnessing the potential of bioinformatics in many areas.
Book Synopsis Computational Genomics with R by : Altuna Akalin
Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Book Synopsis Use of High-throughput Sequencing Technologies to Study the Genetic Basis of Monogenic and Complex Diseases by : Ellen Rachel Amy Thomas
Download or read book Use of High-throughput Sequencing Technologies to Study the Genetic Basis of Monogenic and Complex Diseases written by Ellen Rachel Amy Thomas and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Biological Sequence Analysis by : Richard Durbin
Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Genome Sequencing Technology and Algorithms by : Sun Kim
Download or read book Genome Sequencing Technology and Algorithms written by Sun Kim and published by Artech House Publishers. This book was released on 2008 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2003 completion of the Human Genome Project was just one step in the evolution of DNA sequencing. This trailblazing work gives researchers unparalleled access to state-of-the-art DNA sequencing technologies, new algorithmic sequence assembly techniques, and emerging methods for both resequencing and genome analysis.
Book Synopsis Mapping and Sequencing the Human Genome by : National Research Council
Download or read book Mapping and Sequencing the Human Genome written by National Research Council and published by National Academies Press. This book was released on 1988-01-01 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is growing enthusiasm in the scientific community about the prospect of mapping and sequencing the human genome, a monumental project that will have far-reaching consequences for medicine, biology, technology, and other fields. But how will such an effort be organized and funded? How will we develop the new technologies that are needed? What new legal, social, and ethical questions will be raised? Mapping and Sequencing the Human Genome is a blueprint for this proposed project. The authors offer a highly readable explanation of the technical aspects of genetic mapping and sequencing, and they recommend specific interim and long-range research goals, organizational strategies, and funding levels. They also outline some of the legal and social questions that might arise and urge their early consideration by policymakers.
Book Synopsis Development of a High Throughput Sequencing Infrastructure for the Analysis of Complex Genomes by : HyeRan Kim
Download or read book Development of a High Throughput Sequencing Infrastructure for the Analysis of Complex Genomes written by HyeRan Kim and published by . This book was released on 2003 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis High Throughput Gene Screening by : Valerie Carabetta
Download or read book High Throughput Gene Screening written by Valerie Carabetta and published by Humana. This book was released on 2024-12-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores the latest advancements in the high-throughput sequencing (HTS) technologies and its uses in our understanding of complex biological processes and human diseases. The chapters in this book are organized into five parts and cover topics such as genome based-sequencing technologies, including whole genome sequencing, targeted sequencing, and metagenomic analysis; epigenome-based technologies like EM-seq, MNase-seq, and ATAC-seq; transcriptome-based sequencing technologies, including RNA-seq, scRNA-seq, mi-RNA-seq and RIL-seq; HTS modalities for structural studies of DNA including Hi-C and DamID-seq; and the potential use of HTC in clinical settings, including cancer research and treatment, and personalized medicine. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, tips on troubleshooting, and avoiding known pitfalls. Cutting-edge and thorough, High Throughput Gene Screening: Methods and Protocols is a valuable resource for all researchers interested in incorporating HTS into their research and learning more about this exciting technology.
