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Fero Lab Custom R packages
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1. Install R on your computer:
This page contains links to custom packages that may be used with R statistical software
and Bioconductor to analyze array data. Before being
able to use them you will need to install R on your
computer.
R
homepage
Everything you wanted to know about R but were afraid to ask.
R
download and Installation
From the FHCRC mirror
Bioconductor
homepage
Packages and vinettes from Bionconductor are available here or may be
downloaded from within the R program.
2. Download custom packages and
instructions:
Use the following links to download or learn more about
our custom R source packages. Instructions for installing the
packages are also given, below.
ArrayFun:
A package to
analyze 2-color expression arrays (cDNA or oligonucleotide) starting
with raw (.gpr) data. Includes layout data for the FHCRC murine
15k, and 22k cDNA arrays obviating the need for GAL files on these
platforms.
BACarray:
A package to analyze
CGH arrays (2-color arrays) starting with raw data (.gpr files).
Includes layout data from the FHCRC human BAC array.
HomoVert:
A package to convert
Entrez Gene IDs from one species to another. It has a builtin
Homologene conversion table and a function to convert your Gene IDs to
a second species of your choice. Also outputs gene symbol,
protein ID
and protein accession numbers.
3. Install custom packages:
1. Install and launch R (See R download and Installation,
above).
2. Download one of the Custom Packages, above, (e.g. 'ArrayFun') to your
home folder.
3. Install the custom packagea. Mac OS (using R.app)
From within R.app select:
Packages & Data > Package Installer
From the Installer window choose:
Packages Repository > Local Source Package
Install... (browse to the Source package in your
home
folder.)
b. Using Linux, Mac OS Terminal or Mac
OS X11:
Type: R
CMD Install ArrayFun_x.y.tar.gz
If you get an error 'Error: object "R" not found' then
you have not installed R correctly (e.g. it has not been added to your
path).
Once the process is complete you will see the
message: "DONE
(Package name)".
c. Using Windows:
Installing source packages under
Windows is possible but requires extra software tools. See the R for
Windows FAQ for more information. If you know an R programmer
who uses Windows you could ask him or her to compile the package and
give you the resulting binary file which should be easier to install.
4. Using custom packages:
1. Launch R.app (Mac OS) from the /Applications folder. (Alternatively type R in a Terminal or X11 window.)
2. Into the console type:
library(ArrayFun) # or one of the other Packages
3. For information you can either:
a. See one of the PDF manuals above,
b. Type ?ArrayFun into the
console (or other package name),
or
c. Type ArrayFun
into the search field at the top of the R.app window.