Difference between revisions of "BioConductor/R framework"
From Organic Design wiki
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*The project started in the autumn of 2001 | *The project started in the autumn of 2001 | ||
*Includes 23 core collaborating developers | *Includes 23 core collaborating developers | ||
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=====Bioconductor Goals===== | =====Bioconductor Goals===== | ||
The broad goals of the project are: | The broad goals of the project are: | ||
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library(tkWidgets) | library(tkWidgets) | ||
vExplorer() | vExplorer() | ||
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=====Object oriented class method design (''[http://en.wikipedia.org/wiki/Object-oriented_programming OOP]'')===== | =====Object oriented class method design (''[http://en.wikipedia.org/wiki/Object-oriented_programming OOP]'')===== | ||
*Organized approach to handling large amounts of experimental data | *Organized approach to handling large amounts of experimental data | ||
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*Allows efficient representation and manipulation (''including subsetting'') of data from many microarray slides in an experiment | *Allows efficient representation and manipulation (''including subsetting'') of data from many microarray slides in an experiment | ||
*A method is a function that performs an action on data (''objects'') throughout analysis | *A method is a function that performs an action on data (''objects'') throughout analysis | ||
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=====Advantages===== | =====Advantages===== | ||
*Newest cutting edge statistical methods available | *Newest cutting edge statistical methods available | ||
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*Powerful graphical tools available | *Powerful graphical tools available | ||
*Its freely available | *Its freely available | ||
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=====Disadvantages===== | =====Disadvantages===== | ||
*Steep learning curve | *Steep learning curve | ||
*Need to have experience programming in the R programming environment (''http://www.r-project.org'') | *Need to have experience programming in the R programming environment (''http://www.r-project.org'') | ||
*Like all software there are bugs | *Like all software there are bugs | ||
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=====Accessing Bioconductor===== | =====Accessing Bioconductor===== | ||
*Bioconductor tools are accessed using the R programming language | *Bioconductor tools are accessed using the R programming language | ||
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getBioC() <font color="red">''# Running script''</font> | getBioC() <font color="red">''# Running script''</font> | ||
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=====Installing vs loading packages===== | =====Installing vs loading packages===== | ||
*Packages only need to be installed once onto a computer | *Packages only need to be installed once onto a computer | ||
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*The R function ''library'' is used to load packages e.g. | *The R function ''library'' is used to load packages e.g. | ||
library(limma) <font color="red"> #Installs the limma package </font> | library(limma) <font color="red"> #Installs the limma package </font> | ||
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=====Documentation and Help===== | =====Documentation and Help===== | ||
*R [http://cran.stat.auckland.ac.nz/manuals.html manuals] and [http://cran.stat.auckland.ac.nz/other-docs.html tutorials] are available from the [http://cran.stat.auckland.ac.nz R] website or on-line in an R session | *R [http://cran.stat.auckland.ac.nz/manuals.html manuals] and [http://cran.stat.auckland.ac.nz/other-docs.html tutorials] are available from the [http://cran.stat.auckland.ac.nz R] website or on-line in an R session | ||
Revision as of 01:50, 14 March 2006
What is Bioconductor? (http://www.bioconductor.org)
- Bioconductor is an open source development software project
- Provides tools for analysis and comprehension of genomic data
- Extensively for Affymetrix and cDNA microarray technologies
- The project started in the autumn of 2001
- Includes 23 core collaborating developers
Bioconductor Goals
The broad goals of the project are:
- To enable sound and powerful statistical analyses in genomics
- To provide a computing platform that allows the rapid design and deployment of high-quality software
- To develop a computing environment for both biologists and statisticians
- Promote high-quality dynamic documentation and reproducible research
- Using LATEX, the Sweave system and tcl/tk to deliver interactive step by step pdf tutorials, e.g.
library(tkWidgets) vExplorer()
Object oriented class method design (OOP)
- Organized approach to handling large amounts of experimental data
- Class structure encapsulates the data required for microarray analysis → object
- Allows efficient representation and manipulation (including subsetting) of data from many microarray slides in an experiment
- A method is a function that performs an action on data (objects) throughout analysis
Advantages
- Newest cutting edge statistical methods available
- Modern programming language
- Powerful graphical tools available
- Its freely available
Disadvantages
- Steep learning curve
- Need to have experience programming in the R programming environment (http://www.r-project.org)
- Like all software there are bugs
Accessing Bioconductor
- Bioconductor tools are accessed using the R programming language
- R is a programming environment for statistical computing and graphics
- Initially written by Robert Gentleman and Ross Ihaka (Auckland University)
- Download R from a Comprehensive R archive network (CRAN) mirror (http://cran.stat.auckland.ac.nz)
- Install R (available for Unix, Windows, and Mac OS X)
- R version 2.2.1 has been released on 2005-12-20
- R is the environment used to design and distribute software:
- Locally downloaded files
- Via the internet e.g. Commands in R
# Setting proxy variable # Downloading installation script
getBioC() # Running script
Installing vs loading packages
- Packages only need to be installed once onto a computer
- Packages must be loaded with each new R session
- The R function library is used to load packages e.g.
library(limma) #Installs the limma package
Documentation and Help
- R manuals and tutorials are available from the R website or on-line in an R session
- R on-line help system, detailed high quality on-line documentation, available in text, HTML, PDF, and LATEX formats.
help.start() # Browser based help documentation help() # Help on a topic ? ls # alternative help method on ls function apropos(mean) # Find Objects by (Partial) Name example(mean) # Run an Examples Section from the Online Help demo() # Demonstrations of R Functionality demo(graphics) # Demonstration or graphics Functionality
- Email news lists for Bioconductor / R
- Note: Read the posting guides before submitting questions
- Frequently asked questions Bioconductor / R
