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Statistical Analysis of Next Generation Sequencing Data

  • Somnath Datta
  • Dan Nettleton

Part of the Frontiers in Probability and the Statistical Sciences book series (FROPROSTAS)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Riten Mitra, Ryan Gill, Susmita Datta, Somnath Datta
    Pages 1-24
  3. Douglas J. Lorenz, Ryan S. Gill, Ritendranath Mitra, Susmita Datta
    Pages 25-49
  4. Yunshun Chen, Aaron T. L. Lun, Gordon K. Smyth
    Pages 51-74
  5. Andrea Riebler, Mark D. Robinson, Mark A. van de Wiel
    Pages 75-91
  6. Dan Nettleton
    Pages 93-113
  7. Alyssa C. Frazee, Leonardo Collado Torres, Andrew E. Jaffe, Ben Langmead, Jeffrey T. Leek
    Pages 115-128
  8. Hao Xiong, James Bentley Brown, Nathan Boley, Peter J. Bickel, Haiyan Huang
    Pages 129-143
  9. Davide Risso, John Ngai, Terence P. Speed, Sandrine Dudoit
    Pages 169-190
  10. Peng Liu, Yaqing Si
    Pages 191-217
  11. Kean Ming Tan, Ashley Petersen, Daniela Witten
    Pages 219-246
  12. Riten Mitra, Peter Müller
    Pages 297-314
  13. Ruofei Du, Zhide Fang
    Pages 335-353
  14. Debashis Ghosh, Santhosh Girirajan
    Pages 405-422
  15. Back Matter
    Pages 423-432

About this book

Introduction

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.

Keywords

Copy Number Variation DNA Genomics Isoform Expression Detection RNA Sequencing Data

Editors and affiliations

  • Somnath Datta
    • 1
  • Dan Nettleton
    • 2
  1. 1.Department of Bioinformatics and BiostatisticsUniversity of LouisvilleLouisvilleUSA
  2. 2.Department of StatisticsIowa State UniversityAmesUSA

Bibliographic information