1 Installation of R packages

If not done already, installed recent versions of R or RStudio on your computers via ZDV-Apps. Do not forget to logout and then login again, before you lunch them.

For the tutorials on ChiP-seq and gene expression analysis, you need to install several packages from Bioconductor, an open-source software development project that provides tools for the analysis and comprehension of high-throughput genomic data. Other useful R packages and documentation are available from the Comprehensive R Archive Network CRAN.

ChiP-seq

# install standard R packages:
install.packages("ggplot2") # for plotting
install.packages("reshape") # for Venn diagrams
install.packages("Vennerable", repos="http://R-Forge.R-project.org")    # for Venn diagrams

# vector of Bioconductor package names:
pkgs <- c(
"rtracklayer",
"TFBSTools",
"JASPAR2014",
"BSgenome.Hsapiens.UCSC.hg18",
"TxDb.Hsapiens.UCSC.hg18.knownGene"
)

# install BioConductor packages:
source("http://bioconductor.org/biocLite.R")
biocLite(pkgs, suppressUpdates=TRUE)

Gene expression

# set two lists with the names of the Biocodnuctor and the CRAN packages
bioc.libs <- c("Biobase", "affy", "annotate", "hgu95av2.db", "hgu95av2cdf", "estrogen",
               "limma", "genefilter", "vsn", "GEOquery", "annaffy", "GO.db","KEGG.db")
cran.libs <- c("RColorBrewer", "R.utils", "gplots")

Before we continue with installing, lets check for available updates on the already available packages, using the function biocLite from the Bioconductor package BiocInstaller. If invoked with no arguments it installs core packages (when Bioconductor is installed for the first time) or updates already installed packages.

source("http://bioconductor.org/biocLite.R") # get BiocInstaller
biocLite() # if they are outdated packages, choose the option to update all the packages

After the update, restart the R session (in RStudio go to menu tab Session -> Restart R). Now load the BiocInstaller package and finally install the packages saved in the lists above.

library(BiocInstaller)
biocLite(bioc.libs)
biocLite(cran.libs)

After successful installation, restart the R session again, and check the status of the available packages: in your case, everything should be up to date.

library(BiocInstaller)
biocValid() # should return TRUE

2 Downloading Cytoscape installation files

For the exercises on course day 9 about networks you need to install Cytoscape.

  1. Open a web browser and type the following line into the address bar: \\uni-mainz.de\dfs\Setup\Software Cytoscape\.
  2. Copy the installation file Cytoscape_3_3_0_windows_64bit.exe into the local folder C:\Users\Public.
  3. Do not install Cytoscape now! You will do this on day 9.
  4. Open ZDV-Apps and install “Java RE8 x64”.

3 R help

A short reminder on how to get help for various topics (e.g., packages, functions, operators, concepts) as follows
help() or ? is primary help for functions and features,
help.search() or ?? finds help pages on a vague topic,
library() lists available packages and the help objects they contain,
data() lists available data sets,
ls lists names of the objects in a specified environment.

help(package="affy") # get help even when package is not loaded
?? affy
help.search("affy") 
? sapply #help(sapply)  
#' some topics, such as operators or control-flow reserved words, need to be quoted
? "if"
? "+"
## open the vignette for the Biobase package (the package has to be already attached)
library(Biobase) # base functions for Bioconductor
openVignette("Biobase") 

4 References

Hahne et al. (2008). Bioconductor case studies
Huber et al. (2015). Orchestrating high-throughput genomic analysis with Bioconductor
Bioconductor training materials, courses on (various) genomic data analysis.
RStudio cheat sheets, useful if you plan to use RStudio more often.
Cytoscape 3 User Tutorials, for getting started with Cytoscape.


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