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Titlebook: Statistical Analysis of Next Generation Sequencing Data; Somnath Datta,Dan Nettleton Book 2014 Springer International Publishing Switzerla

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發(fā)表于 2025-3-21 19:11:23 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Statistical Analysis of Next Generation Sequencing Data
編輯Somnath Datta,Dan Nettleton
視頻videohttp://file.papertrans.cn/877/876347/876347.mp4
概述Provides statistical tools for working with the latest research data in NGS.Contains chapters written by leading statisticians in the field of NGS.Useful for students and researchers that work in biom
叢書名稱Frontiers in Probability and the Statistical Sciences
圖書封面Titlebook: Statistical Analysis of Next Generation Sequencing Data;  Somnath Datta,Dan Nettleton Book 2014 Springer International Publishing Switzerla
描述.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 Statisti
出版日期Book 2014
關(guān)鍵詞Copy Number Variation; DNA; Genomics; Isoform Expression Detection; RNA; Sequencing Data
版次1
doihttps://doi.org/10.1007/978-3-319-07212-8
isbn_softcover978-3-319-37905-0
isbn_ebook978-3-319-07212-8Series ISSN 2624-9987 Series E-ISSN 2624-9995
issn_series 2624-9987
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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Detecting Copy Number Changes and Structural Rearrangements Using DNA Sequencing,o present a method for the detection of somatic structural rearrangement. We will illustrate these methods using data from breast cancer cell line (tumor) along with its blood (normal) counterpart generated by the cancer cell-line encyclopedia project.
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Statistical Methods for the Analysis of Next Generation Sequencing Data from Paired Tumor-Normal Saiations at the DNA level using paired tumor and normal sequencing data, including single nucleotide alterations (SNAs) and copy number alterations (CNAs). We describe selected statistical methods, their strengths and limitations, and discuss future directions.
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發(fā)表于 2025-3-22 11:09:58 | 只看該作者
Design of RNA Sequencing Experiments, biological replication over both technical replication and increased sequencing depth per experimental unit provide improved assessments of differential expression. Several example experimental designs are presented to illustrate the featured design principles.
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MOSAiCS-HMM: A Model-Based Approach for Detecting Regions of Histone Modifications from ChIP-Seq Dased approach for modeling read counts in histone modification ChIP-seq experiments and accounts for the spatial dependence in their ChIP-seq profiles. In addition, its . package implementation provides many functionality for summarizing these data and generating files that can be directly uploaded to the UCSC genome browser.
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