Introduction to bioinformatics with R : a practical guide for biologists / Edward Curry.

By:

Curry, Edward R [author.]

Material type: Text

TextSeries: Chapman & Hall/CRC mathematical and computational biologyPublication details: NW : CRC Press, c2021.Edition: First editionDescription: 1 online resourceISBN:

9781351015318

Subject(s):

Additional physical formats: Print version:: Introduction to bioinformatics with RDDC classification:

570.285 23 CUR

LOC classification:

QH324.2

Contents:

Introduction Introduction to R An Introduction to LINUX for Biological Research Statistical Methods for Data Analysis Analyzing Generic Tabular Numeric Datasets in R Functional Enrichment Analysis Integrating Multiple Datasets in R Analyzing Microarray Data in R Analyzing DNA Methylation Microarray Data in R DNA Analysis With Microarrays Working with Sequencing Data Genomic Sequence Profiling ChIP-seq RNA-seq Bisulphite Sequencing Final Notes

Summary: "This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. Through the entire book, theoretical explanations are presented alongside step-by-step instructions for carrying out a number of widely-applicable data analysis tasks using freely available software. This book guides the reader through the basic principles of exploratory analysis and hypothesis testing in high-dimensional datasets, and the practicalities of installing statistical computing software and using this to handle different types of data tables"--

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
General Books	CUTN Central Library Sciences	Non-fiction	570.285 CUR (Browse shelf(Opens below))	Available		47295

"A Chapman and Hall book."

Includes bibliographical references and index.

Introduction

Introduction to R

An Introduction to LINUX for Biological Research

Statistical Methods for Data Analysis

Analyzing Generic Tabular Numeric Datasets in R

Functional Enrichment Analysis

Integrating Multiple Datasets in R

Analyzing Microarray Data in R

Analyzing DNA Methylation Microarray Data in R

DNA Analysis With Microarrays

Working with Sequencing Data

Genomic Sequence Profiling

ChIP-seq

RNA-seq

Bisulphite Sequencing

Final Notes

"This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. Through the entire book, theoretical explanations are presented alongside step-by-step instructions for carrying out a number of widely-applicable data analysis tasks using freely available software. This book guides the reader through the basic principles of exploratory analysis and hypothesis testing in high-dimensional datasets, and the practicalities of installing statistical computing software and using this to handle different types of data tables"--

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