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These notes describe how we configured a custom AMI for running Coexpression on EC2.
...
also need "sma" which is available here:
http://cran.r-project.org/src/contrib/Archive/sma/
... but it won't build (!)
... so we got the version from Belltown and put it here
"/usr/local/lib64/R/library"
Note: We also installed the WGCNA package from UCLA and a 'packaged' version of Bin Zhang's coexpression code.
copied
C:\Users\bhoff\eclipse projects\trunk\client\rSynapseClient
to
/usr/local/ec2-home
...
datasets <- getDatasets()
dsId <- datasets$dataset.id[PLFM:datasets$dataset.name == "Harvard Brain Tissue Resource Center"]
ds <- getDataset(dsId)
layers <- getDatasetLayers(ds)
## hack
## get the expression layer and load it
layers <- layers$results
layerType <- NULL
for(i in 1:length(layers)){
layerType[i] <- layers[[PLFM:i]]$type
}
layers <- layers[PLFM:which(layerType == "E")]
for(i in 1:length(layers)){
#look for gene expression layer
indx <- grep("Agilent 44K",layers[[PLFM:i]]$platform)
if(length(indx) == 0) next
break
}
layers <- layers[[PLFM:i]]
exprLayerFiles <- synapseClient:::.cacheFiles(entity=layers)
...