A Practical Guide to Cancer Systems Biology

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92 A Practical Guide to Cancer Systems Biology



  1. Installation of relevant R packages


Several R packages have been made available via Bioconductor,^1 an
open source framework for bioinformatics implemented in R. To source
Bioconductor in the R session, enter the following command:



source(“http://www.bioconductor.org/biocLite.R”)



Then you can install specific packages, e.g., an R package ALL, which
contains a gene expression dataset about patients with leukemia,^2 via the
function biocLite() as follows:



biocLite(“ALL”)



The package ALL will be downloaded into your computer. Other R packages
that we use in this chapter include hgu95av.db, org.Hs.eg.db, samr, GOstats,
KEGG.db, and Rgraphviz, and should be downloaded with the following
commands:



biocLite(“hgu95av.db”)
biocLite(“org.Hs.eg.db”)
biocLite(“samr”)
biocLite(“GOstats”)
biocLite(“KEGG.db”)
biocLite(“Rgraphviz”)




  1. Getting the gene expression dataset


To get started with a gene expression dataset, load the package ALL using
the function library():



library(ALL)



Now, ALL package has been loaded to your computer, but not to R. To see
all available data sets in the ALL package, enter the command:



data(package=“ALL”)



You can see there is a data set called ALL in this package. To load this data
set into R, use the command:



data(ALL)



Enter the command to learn more details about this data set ALL:



ALL



ExpressionSet (storageMode: lockedEnvironment)
assayData: 12625 features, 128 samples

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