Bioinformatics and Computational Biology Solutions Using R and Bioconductor [Hardcover]

Robert Gentleman (Editor), Vincent Carey (Editor), Wolfgang Huber (Editor), Rafael Irizarry (Editor), Sandrine Dudoit (Editor)

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Product Details

Hardcover: 492 pages
Publisher: Springer; 1 edition (Aug 31 2005)
Language: English
ISBN-10: 0387251464
ISBN-13: 978-0387251462
Product Dimensions: 23.7 x 16.1 x 3.1 cm
Shipping Weight: 898 g
Amazon Bestsellers Rank: #120,153 in Books (See Top 100 in Books)
- #12 in Books > Science > Biological Sciences > Bioinformatics
- #64 in Books > Medicine > Research > Biostatistics
- #64 in Books > Science > Biological Sciences > Biostatistics

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Review

From the reviews: "The book has several nice touches that readers will appreciate. First, the liberal use of color shows the full capabilities of Bioconductor pakages and brings the material to life. Second, color figures are dispersed throughout the text rather than being relegated to a central section of color plates. Third, the index indicates whether a term references a package, function or class. This book is an excellent resource... In summary, this book is a must have for any Bioconductor user." (J. Wade Davis, Journal of the American Statistical Association, Vol. 102, No. 477, 2007) "This book is solid evidence of the influence that quantitative researchers can have on biological investigations. Organized into separate chapters of shared authorship, the book provides a valuable overview of the impact that the authors and their colleagues have had on the analysis of genomic data." (R.W. Doerge, Biostatistics, December 2006) "This book provides an in-depth demonstration of the potential of the Bioconductor project, through a varied mixture of descriptions, figures and examples. … The book … is an exciting opportunity for researchers to learn directly from the software developers themselves. The range of material covered by the book is diverse and well structured. An abundance of fully worked case studies illustrate the methods in practice. … it should be a must for any researcher considering getting started with the software … ." (Rebecca Walls, Journal of Applied Statistics, Vol. 34 (3), 2007) "The book provides an extensive overview over the most important tasks in analyzing genomic data with Bioconductor. … The book is well written and communicates hands-on experience of the developers of the respective Bioconductor packages themselves. … The book is targeted to a broad range of researchers interested in genomic data analysis, including biologists, bioinformaticians, and statisticians. … It is a very valuable resource for modern genomic data analysis. There is no comparable book on the market." (Jörg Rahnenführer, Statistical Papers, Vol. 50, 2009)

Product Description

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

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Most Helpful Customer Reviews on Amazon.com ^(beta)

Amazon.com: 2.4 out of 5 stars (5 customer reviews)

24 of 25 people found the following review helpful

4.0 out of 5 stars Book contains many chapters to help get you started, Jun 29 2006

By A. Smith - Published on Amazon.com

This review is from: Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Hardcover)

I purchased this book to learn specific details and look at applications for the functions present in bioconductor. I have had trouble applying some of the chapters to custom data because they are written for specific microarray/data formats. Overall, this book is a good value because it contains examples of how bioconductor can be used to aid in hypothesis testing, but I struggle to apply what I have read to the different types of data I have. The section on Statistical analysis for genomic experiments and the section on gaphs and networks should be the reason you purchase this book. They are very helpful and interesting. The case studies were not very helpful in my opinion.

15 of 16 people found the following review helpful

2.0 out of 5 stars technically accurate but pedagogically flawed, Feb 8 2007

By M. Driscoll - Published on Amazon.com

This review is from: Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Hardcover)

If you're like me, you came upon this book because you decided to use R for analysis of microarray data, but you're mired in its gory and frustrating details.

Yes, you need a reference book. But not this one, and certainly not this edition. Better documentation can be found elsewhere (dare I say online?).

The code examples given are technically accurate and run as advertised, but they are of the "monkey see, monkey do" variety. They provide little intuition for how to use R for oneself, outside the covers of this text. For example, Chapter 23 discusses linear models for microarray data (using the "limma" package), and several code examples contain the parameter 'adjust = "fdr"'. The reader is never enlightened that this refers to a "false discovery rate" adjustment.

In other cases, example code is simply missing. Chapter 21 covers the Rgraphviz graphing library, with a figure showing the three common graphical layouts -- but no example code for producing these graphs is given (I had to find it outside the book).

For those trying to use R for computational biology, I recommend getting an overview of the R programming language first (Venables and Ripley's book "Modern Applied Statistics with S" is a great text), and only then wading into references such as this one, if at all.

1 of 1 people found the following review helpful

4.0 out of 5 stars extremely helpful, but suffers from multiple author problem, Feb 10 2009

By Lisa Jones - Published on Amazon.com

This review is from: Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Hardcover)

This book is great for helping you get started analyzing all types of microarrays in R. However, the chapters are written by several different authors which causes the book to be a little disorganized. This is probably the case with many books that have contributed chapters. In the end, the technical information is there, sometimes you just have to visit a couple of different chapters.

› Go to Amazon.com to see all 5 reviews 2.4 out of 5 stars