<strong>Textual Statistics with R</strong> comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is i
R Programming for Bioinformatics (Chapman & Hall/CRC Computer Science & Data Analysis)
β Scribed by Robert Gentleman
- Publisher
- Chapman and Hall/CRC
- Year
- 2008
- Tongue
- English
- Leaves
- 327
- Series
- Chapman & Hall/CRC Computer Science & Data Analysis
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
R itself is well equipped with documentation, which ships with every
distribution of R and the R add-on packages. But a good overall
picture, how R concrete is used in nowadays bioinformatics software
development, was always missing.
If you are interested in bioinformatics software developing, and you
aren't looking for a book which is just explaining how to do standard
biological data analysis within R, or how to solve statistical
problems whit R, but how to implement R-code for the biological
research field - this is the book! The book goes in a reasonable deep
through the whole guts of the R language and the core of the
bioconductor project. Detailed material can then always be found in
the substantial official documentation.
This book was written by a master wizard of the filed - Robert
Gentleman, R developer form the beginning on and member of the
[...] project core team.
Recently another book - R in a Nutshell, which promises to go through
the R guts in a same manner, was published by the famous O'Reilly. I
haven't read 'R in a Nutshell' yet, so I can't compare. However, to
bioinformaticians whit a programmer's angle I can warmly recommend 'R
Programming for Bioinformatics'. For me it was a pleasure to read. And
it remains one of the best guideline and source to start tackling R
software development challenges, in unfamiliarly and new informatics
fields.
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