- Series: Chapman & Hall/CRC Computer Science & Data Analysis
- Hardcover: 328 pages
- Publisher: Chapman and Hall/CRC; 1 edition (July 14, 2008)
- Language: English
- ISBN-10: 1420063677
- ISBN-13: 978-1420063677
- Product Dimensions: 6.2 x 0.9 x 9.3 inches
- Shipping Weight: 1.2 pounds (View shipping rates and policies)
- Average Customer Review: 3.1 out of 5 stars See all reviews (7 customer reviews)
- Amazon Best Sellers Rank: #1,014,696 in Books (See Top 100 in Books)
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R Programming for Bioinformatics (Chapman & Hall/CRC Computer Science & Data Analysis) 1st Edition
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Top Customer Reviews
I think the majority of R users (biologists and programmers) want to run through some common statistical routines in a procedural fashion and produce reports that perform some analysis and show some graphs. The difficulty with R is learning how to massage data into a form that an existing statistical function will accept. That will invariably involve helper R-specific helper functions that do not exist in programming languages (e.g. unsplit) or that require a precise understanding of input (e.g. xtabs), and statistical routines that almost never return meaningful errors (glm). Manipulating data structures in R is not particularly intuitive (e.g. as.numeric(levels(f))[f]), so tons of examples are a must. However this book simply does not include enough R code - probably fewer than 250 lines.
In some instances commands are discussed at length in the space it would take to simply show the command. For example, a beginner would want to know how to save a data frame. Instead of providing a useful example like:
save(myDataFrame,file="myDataFrame.frame.Read more ›
Anyway, this book is well organized and clearly written. As for bioinformatics, the author is not only a co-creator of R, he is a leading figure of the Bioconductor project. Suitable for a bioinformatics-oriented book, it has a whole big chapter on working with character data (not something discussed at great length in other R books, and a very useful chapter on Data Techniques replete with real-life Bioconductor examples. The chapter on OOP comes early in the book and, while does not go into too many details, it is enough to get you going sooner rather than later.
As a conclusion: potential buyers should be careful about whether the content of this book is what thy need. Those who do will probably be happy with the way it is written.
Chapter 3, on "Object-Oriented Programming in R", I find effectively unreadable. In 3.2 appears "Inheritance allows new classes to extend, often by adding new slots...". Aside from the misuse of the transitive verb and the dangling participle, the author nowhere bothers to define "slot", but continues to use it thereafter. If he had decided for whom he is writing the book and that it was an audience advanced enough to have used an OOP language, he might have said "In R, "slot" refers to what is called a "member" in Java or C++." Then he starts talking about "dispatch", only some time later casually "defining" it two or three times. The trouble with this approach is that you never work out what you're supposed to know already, and finally decide that the author himself doesn't know or care. It would be far better to have a book of which the first third is elementary, but systematic, lead-in that you can skip if sufficiently advanced, and the second two thirds is useful stuff that refers back to the earlier material.Read more ›
Nb. I purchased a paper copy of this book and have access to it online via a subscription service.
Most Recent Customer Reviews
R itself is well equipped with documentation, which ships with every
distribution of R and the R add-on packages. Read more
My only concern is that it at various stages the book feels like a programming book on S instead of on R. It needs better editing... Read morePublished on October 7, 2009 by Oracle Frenkenstein