Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R: 1st Edition (Paperback) book cover

Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

1st Edition

By Hongmei Zhang

Chapman and Hall/CRC

200 pages | 40 B/W Illus.

Purchasing Options:$ = USD
Paperback: 9780367495169
pub: 2020-06-03
Available for pre-order. Item will ship after 3rd June 2020
Hardback: 9781498772594
pub: 2020-07-30
Available for pre-order. Item will ship after 30th July 2020

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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.


· 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.

Table of Contents

Genome-Scale Genetic and Epigenetic Data. Methods for Data Pre-Processing. Data Mining. Genetic and Epigenetic Factor Selections. Network Construction and Analyses.

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.

About the Series

Chapman & Hall/CRC Computational Biology Series

This series aims to capture new developments in computational biology, as well as high-quality work summarizing or contributing to more established topics. Publishing a broad range of reference works, textbooks, and handbooks, the series is designed to appeal to students, researchers, and professionals in all areas of computational biology, including genomics, proteomics, and cancer computational biology, as well as interdisciplinary researchers involved in associated fields, such as bioinformatics and systems biology.

For more information or to submit a book proposal, please contact <a href="[email protected]">Elliott Morsia</a> ([email protected]).

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Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
SCIENCE / Life Sciences / Biology / General
SCIENCE / Biotechnology