Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R (Chapman & Hall/CRC Mathematical and Computational Biology)

Hongmei Zhang

ISBN 10: 0367495163 / ISBN 13: 9780367495169

Published by Chapman and Hall/CRC 2020-06-03, 2020

About this Item

Seller Inventory # 6666-IUK-9780367495169

Bibliographic Details

• Title: Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R (Chapman & Hall/CRC Mathematical and Computational Biology)
• Publisher: Chapman and Hall/CRC 2020-06-03
• Publication Date: 2020
• Language: English
• ISBN 10: 0367495163
• ISBN 13: 9780367495169
• Binding: Paperback
• Condition: New

About this title

Synopsis

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline" of analytical methods with concrete examples starting from raw gene expression and DNA methylation data at the genome scale. Methods on quality control, data pre-processing, data mining, and further assessments are presented in the book, and R programs based on simulated data and real data are included. Codes with example data are all reproducible.

Features:

· Provides a sequence of analytical tools for genome-scale gene expression data and DNA methylation data, starting from quality control and pre-processing of raw genome-scale data.

· Organized by a parallel presentation with explanation on statistical methods and corresponding R packages/functions in quality control, pre-processing, and data analyses (e.g., clustering and networks).

· Includes source codes with simulated and real data to reproduce the results. Readers are expected to gain the ability to independently analyze genome-scaled expression and methylation data and detect potential biomarkers.

This book is ideal for students majoring in statistics, biostatistics, and bioinformatics and researchers with an interest in high dimensional genetic and epigenetic studies.

About the Author

Hongmei Zhang is a Biostatistician at the University of Memphis. She has been working with gene expression and DNA methylation data and her methodological research interest is to develop corresponding statistical methods. She has been teaching courses in this field for a number of years.