This workflow reads a CSV file containing microarray data into R, calculates gene level frequencies and plots these as a histogram. /* * Clean up the output of MaxdBrowse */ StringBuffer sb = new StringBuffer(in); //Get rid of crap from start of the file int i = sb.indexOf("Feature_ID"); sb.delete(0, i); //Get rid of crap at the end of the file sb.delete(sb.indexOf("#"), sb.length()); //Convert into csv String maxd = sb.toString(); maxd = maxd.trim(); maxd = maxd.replaceFirst("Feature_ID", "FeatureID"); maxd = maxd.replaceFirst("Normalised data", "NormalisedData"); maxd = maxd.replaceAll("\t", ","); //Remove end commas String[] maxdLines = maxd.split("\n"); StringBuffer newMaxd = new StringBuffer(); for(int x = 0; x < maxdLines.length; x ++) { String line = maxdLines[x]; if(line.endsWith(",")) { line = line.substring(0, line.length() - 1); newMaxd.append(line + "\n"); } } String out = newMaxd.toString(); in out JC_C-0.07-1_Measurement png(histogram); maxd <- read.csv(file=csv,head=TRUE,sep=",") hist(maxd$NormalisedData, method="jitter", main='Gene expn level frequencies of yeast grown in Carbon-deficient media', xlab='Gene expression level') dev.off() csv histogram Will take a list of Measurement names and a list of Column Types and produce a table. All values are coloured in relation to the a reference. In the list of Measurement names, the first Measurement listed is taken to be the reference. Formatted as text. MeasurementDataTabTextFAST is slower because it also exports Reporter and Gene information. * , ProfilePasswordRequired http://dbkgroup.org/software/maxd/maxdBrowse/sequences/MeasurementDataTabTextFASTEST/wsdl.xml query