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Instant Heat Maps in R How-to
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About This Book
In Detail
R has grown rapidly over the years to become one of the most versatile and valuable tools for data analysis and graphing. One of its many useful features is the heat map representation of numerical data, which is an invaluable tool to discover patterns in data quickly and efficiently.
Instant Heat Maps in R How-to provides you with practical recipes to create heat maps of all difficulty levels by yourself right from the start. At the end of each recipe, you will find an in-depth analysis that will equip you with everything you need to know to frame the code to your own needs.
Instant Heat Maps in R will present you with all the different heat map plotting functions that exist in R. You will start by creating simple heat maps before moving on to learn how to add more features to them. While you advance step-by-step through the well-connected recipes, you will find out which tool suits the given situation best. You will learn how to read data from popular file formats and how to format the data to create heat maps as well as the ways to export them for presentation.
Approach
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Heat Maps in R: How-to is an easy to understand book that starts with a simple heat map and takes you all the way through to advanced heat maps with graphics and data manipulation.
Who this book is for
Heat Maps in R How-to is the book for you if you want to make use of this free and open source software to get the most out of your data analysis. You need to have at least some experience in using R and know how to run basic scripts from the command line. However, knowledge of other statistical scripting languages such as Octave, S-Plus, or MATLAB will suffice to follow along with the recipes. You need not be from a statistics background.
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Information
Instant Heat Maps in R How-to
Instant Heat Maps in R How-to
Copyright Ā© 2013 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: June 2013
Production Reference: 1180613
Published by Packt Publishing Ltd.
Livery Place
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Birmingham B3 2PB, UK.
ISBN 978-1-78216-564-4
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Credits
Author
Sebastian Raschka
Reviewers
John B. Johnston
Kristopher Opron
Acquisition Editor
Martin Bell
Commissioning Editor
Yogesh Dalvi
Technical Editor
Ankita R. Meshram
Project Coordinator
Akash Poojary
Proofreader
Paul Hindle
Production Coordinator
Nitesh Thakur
Cover Work
Nitesh Thakur
Cover Image
Aditi Gajjar
About the Author
Sebastian Raschka is a PhD student at Michigan State University and is pursuing a doctorate in Biochemistry and Computer Science. He works in the field of protein structure modeling and is focused on the specificity of protein-ligand interactions. His research involves the development of a protein-ligand docking software based on a novel approach, where he combines the fields of machine learning, pattern recognition, and data mining.
In his free time, Sebastian works on web development and uses JavaScript among other technologies to develop web applications that are used by Bioinformaticians and Computational Biologists.
About the Reviewers
John Johnston is the Bioinformatics Domain Specialist for the Institute for Cyber-enabled Research at Michigan State University. He specializes in scientific analysis in a high-performance computing environment, and the development of software for the interpretation of biological data. He is an experienced Linux systems administrator and scientific consultant. He previously worked for 18 years as a Senior Groundwater Scientist for several prominent engineering firms, where he specialized in the delineation and mitigation of environmental contamination and site restoration.
Kristopher Opron is a PhD student at Michigan State University studying Computational and Mathematical Biology. For his undergraduate research, he worked under Professor Zachary Burton on molecular dynamics simulations of RNA polymerase II. He is currently working on the development of new computational tools for scientists under Professor Guowei Wei.
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Preface
This book is about the construction of heat maps using the popular statistical programming language R. Heat maps are valuable tools for exploratory data analyses in many different applications, such as gene expression levels or stock market data. Together with powerful clustering methods, heat maps are being used to visually detect interesting patterns at one glance, even in very large data sets with hundreds of variables.
This book is a hands-on guide to provide you with a practical approach to construct such powerful heat maps. You will explore the advanced features of heat maps step-by-step, and detailed explanations on the underlying code at the end of each recipe will provide you with enough information to frame those heat maps as per your needs.
What this book covers
Creating your first heat map in R (Simple) will help you create your first heat maps from a small data set provided in R. You will use different heat map functions in R to get a first impression of their functionalities.
Reading data from different file formats (Intermediate) will help you learn how to read data from various popular file formats. After you have created your first heat maps, it is important to learn how to get your own data into R using differently formatted datasets.
Customizing heat maps (Intermediate) will help you explore more advanced functions to customize the layout of the heat maps. The main focus lies on the usage of different color palettes, but we will also cover other useful features, such as cell notes that will be used in this recipe.
Drawing choropleth maps and contour plots (Intermediate) will help you learn to create choropleth maps of the United States and other countries. Choropleth maps are a great way to visualize data from different regions on a geographical map. Also, you will learn how to visualize a 3D surface using a contour plot.
Exporting for presentation (Simple) will help you export heat maps in various popular image formats. By comparing images with different resolutions and file sizes, you will learn how to find the best-suited format for presenti...
Table of contents
- Instant Heat Maps in R How-to