Statistical Analysis of Next Generation Sequencing Data

Datta, Somnath|Nettleton, Dan

ISBN 10: 3319072110 / ISBN 13: 9783319072111

Published by Springer International Publishing, 2014

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 biomedical research and genomic medicine.

Seller Inventory # 4497812

Bibliographic Details

• Title: Statistical Analysis of Next Generation Sequencing Data
• Publisher: Springer International Publishing
• Publication Date: 2014
• Language: English
• ISBN 10: 3319072110
• ISBN 13: 9783319072111
• Binding: Gebunden
• Condition: New
• Seller catalogs:
  • Mathematik/Naturwissenschaften/Technik/Medizin

About this title

Synopsis

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.

About the Author

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.