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5. Introduction to R and Bioconductor

Outline. Introduction. R and BioconductorA very brief lesson about using RIntroducing BioconductorA sample data analysis. Introduction. Microarray experiments generate huge quantities of data which have to beStored, managed, visualized, processed Many options available. HoweverNo tool satisf

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5. Introduction to R and Bioconductor

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    1. 5. Introduction to R and Bioconductor Statistical methods in plant genomics Zaragoza February 2004 Alex Snchez. Departament dEstadstica. Universitat de Barcelona

    2. Outline Introduction. R and Bioconductor A very brief lesson about using R Introducing Bioconductor A sample data analysis

    3. Introduction Microarray experiments generate huge quantities of data which have to be Stored, managed, visualized, processed Many options available. However No tool satisfies all users needs Trade-off. A tool must be Powerful but user friendly Complete but without too many options, Flexible but easy to start with and go further Available, to date, well documented but affordable

    4. So, what you need is R? R is an open-source system for statistical computation and graphics. It consists of A language A run-time environment with Graphics, a debugger, and Access to certain system functions, It can be used Interactively, through a command language Or running programs stored in script files

    5. http://www.r-project.org/

    6. Some pros & cons Powerful, Used by statisticians Easy to extend Creating add-on packages Many already available Freely available Unix, windows & Mac Lot of documentation Not very easy to learn Command-based Documentation sometimes cryptic Memory intensive Worst in windows Slow at times

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