I am making this slow transition from GWAS findings to expression datasets. We are using an online repository of microarray data from different donors (arrayed for different regions of the brain). And basically we are using a set of genes from the initial GWAS findings and see how it is affecting the expression pattern in different regions of the brain.
I came across this method of z-score transformation of the values in RAW microarray data to make sense of whether the gene is up or down regulated i.e (z-score values were calculated by subtracting the total average intensity of the genes in the microarray from the intensity of each individual gene within a single experiment and dividing the result by the standard deviation (SD) of the measure of all the intensities)
Of the multiple headers in the raw data, i believe (the formula is referring to gProcessedSigError for SD ; gMeanSignal for signal intensity genes in the array)
My question - is these two columns are enough to calculate the z-score or am I missing something. Sorry for a more specific and a basic question. Any suggestions will be of great help
some other columns may be relevance
gSurrogateUsed gIsFound gProcessedSignal gProcessedSigError gNumPixOLHi gNumPixOLLo gNumPix gMeanSignal gMedianSignal gPixSDev gPixNormIQR gBGNumPix gBGMeanSignal gBGMedianSignal gBGPixSDev gBGPixNormIQR gNumSatPix