HTqPCR Installation Guide

These are the installation notes for the HTqPCR package, developed for high-throughput analysis of qPCR data within the R and Bioconductor framework. There are four sections:

1) Installing HTqPCR from Bioconductor: The recommended method
2) Installing HTqPCR directly from file: Installing the file linked from this web page
3) How to use HTqPCR: Getting help and examples
4) Introduction to R and Bioconductor: Some useful links and hints for new R users

For any problems or questions, please contact heidi@ebi.ac.uk or bertone@ebi.ac.uk


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Installing HTqPCR from Bioconductor:

We recommend that users install the package via Bioconductor, since this will automatically detect and install all required dependencies. HTqPCR is available through Bioconductor as of version 2.5 (released October 2009), corresponding to R version 2.10.0. 

The Bioconductor installation procedure is described at: http://www.bioconductor.org/docs/install/ 
To install HTqPCR, first open a new R session, and in a command terminal either type or copy/paste:

source("http://www.bioconductor.org/biocLite.R")
biocLite("HTqPCR")


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Installing HTqPCR directly from a distributed package:

When installing HTqPCR from the source or binary files obtained from this website, both the package itself as well as other Bioconductor dependencies need to be present in the R environment.


Step 1: Installing all dependencies

In an R terminal, type or copy/paste:

source("http://bioconductor.org/biocLite.R")
biocLite(c("Biobase", "RColorBrewer", "limma", "statmod", "affy", "gplots"))
 

Step 2: Installing the HTqPCR package

This procedure will depend on the target operating system.

Unix:
- On the command line, enter "R CMD install HTqPCR_X.tar.gz" (where X is the version number)

Mac OS:
From source:
- On the command line, enter "R CMD install HTqPCR_X.tar.gz" in a terminal (where X is the version number)
(or)
- In the R menu bar: "Packages & Data" -> "Package Installer" -> "Local Source Package" (from the dropdown menu) -> press "Install" -> select "HTqPCR_X.tar.gz" (where X is the version number) from the local directory where the file was saved.

From the precompiled binary:
- In the R menu bar: "Packages & Data" -> "Package Installer" -> "Local Binary Package" (from the dropdown menu) -> press "Install" -> select "HTqPCR.tgz" from the local directory where the file was saved.

Windows:
From source: 
Please see http://cran.r-project.org/doc/manuals/R-admin.html#The-Windows-toolset and http://www.murdoch-sutherland.com/Rtools/

From the precompiled binary:
- In the R menu bar: "Packages" -> "Install package(s) from local zip files..." -> select "HTqPCR_X.zip" from the local directory where the file was saved.


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Getting HTqPCR help and tutorial information:

Before using HTqPCR in R, it is necessary to load the package each time a new R session is started:

library(HTqPCR)

For all functions the R help files can be accessed by typing the name of the function preceded by "?" in an R terminal, e.g.:

?plotCtCard

Likewise, functions in HTqPCR include some examples of their use. These can be viewed at the bottom of the help pages, or run directly from the terminal, e.g.:

example(plotCtCard)

To get a full list of all functions available in the currently installed version of HTqPCR, type:

ls("package:HTqPCR")

The tutorial for HTqPCR is available on this webpage, and can also be accessed within R. If the HTqPCR package is loaded, type:

openVignette()

This will display a list of all tutorials available for the packages that are currently loaded into the R environment. Selecting HTqPCR will then open the tutorial document as a PDF. 

All of the R commands used in the tutorial can be exported and saved to a local file by typing:

all.R.commands <- system.file("doc", "HTqPCR.Rnw", package = "HTqPCR")
Stangle(all.R.commands)

This will create a file called HTqPCR.R in your current working directory, containing examples of all the commands needed to run a typical qPCR analysis.


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Introduction to R and Bioconductor:

R refers to the base statistical framework and language compiler. It contains a selection of default packages for performing various kinds of statistical analysis and visualisation. Bioconductor is a collection of R packages targeted at the analysis of biological data. 

For those not familiar with R and Bioconductor, the primary sources for information and installation are:
http://www.r-project.org/
http://www.bioconductor.org/

Both R and Bioconductor packages are open source and free to download and use. To find the latest release versions of Bioconductor packages, the current selection is listed at http://www.bioconductor.org/download

The main R manual is "An Introduction to R", available through the R-project website under "Documentation" -> "Manuals" in the left-side menu. The Internet is also an abundant source of R tutorials, among them:

- http://courses.washington.edu/fishrw09/Lecture_1_Girvetz-Intro_to_R_Programming_10February2009.ppt
- http://damtp.cam.ac.uk/user/sje30/downloads.html -> "R" -> "Lecture notes"
- http://addictedtor.free.fr/graphiques

The general Bioconductor overview (http://www.bioconductor.org/overview/) describes the purpose and structure of the Bioconductor project.

All Bioconductor packages include associated tutorials, which vary considerably in length and scope. The Bioconductor documentation pages and the FAQ, at http://www.bioconductor.org/docs/faq are useful references, as are documents made available from various Bioconductor workshops at http://www.bioconductor.org/workshops.