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preprocessData.R

Copyright 2013 Allen Institute for Brain Science Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

 

      		
    

    

      
        

          
        

        
Read the CSV data files for a human microarray donor (accessible here: [http://human.brain-map.org/static/download]).
Then run through the list of probes and remove those that have no entrez ID and 
use the collapseRows WGCNA function to pick a single probe per gene.  Also download
some supplementary sample metadata useful for visualization.  Finally save the result
to an R object file.  The following will preprocess the 9861 donor microarray data,
assuming 9861.zip has been unarchived into a directory called 9861.



library(WGCNA)
library(RJSONIO)
source(“preprocessData.R”)
source(“api.R”)
preprocessData(“9861”,“9861.RData”)


      		
      
        
preprocessData <- function(donorDir,outputFileName) {

      		
    

    

      
        

          
        

        
Load in the data for one of the donors.

      		
      
        
  datExpr <- read.csv(sprintf("%s/MicroarrayExpression.csv",donorDir),header=FALSE,row.names=1)
  probeInfo <- read.csv(sprintf("%s/Probes.csv",donorDir),header=TRUE)
  sampleInfo <- read.csv(sprintf("%s/SampleAnnot.csv",donorDir),header=TRUE)

      		
    

    

      
        

          
        

        
Filter the data.  Remove probes that have no entrez id.

      		
      
        
  validProbes = which(probeInfo$entrez_id>=0,arr.ind=TRUE)
  datExpr <- datExpr[validProbes,]
  probeInfo <- probeInfo[validProbes,]

      		
    

    

      
        

          
        

        
Some genes have more than one probe.  The collapseRows function chooses
a single probe to represent a gene.

      		
      
        
  probeNames = probeInfo[which(probeInfo == rownames(datExpr)),"gene_symbol"]
  probeIDs = rownames(datExpr)
  datCollapsed = collapseRows(datExpr, probeNames, probeIDs)

  datExpr <- datCollapsed$datETcollapsed
  probeInfo <- probeInfo[which(datCollapsed$selectedRow == TRUE,arr.ind=TRUE),]
  

      		
    

    

      
        

          
        

        
The API provides structure colors and sort order for visualization purposes.  Download
those value and append them to the sampleInfo data frame.  


      		
      
        
  sampleInfo <- downloadSampleProperties(sampleInfo)

  save(datExpr,probeInfo,sampleInfo,file=outputFileName)
}