# Difference in Calculation through GEO2R and difference in Article

Here is microarray analysis where author uses GSE50632 series on an Agilent microarray GPL17660 platform with 4 eligible samples which I guess are GSM1224991, GSM1224992, GSM1224993 and GSM1224994 among which two are healthy and two are patient samples.

However I found the difference in the calculations-

Through GEO2R analysis table it is-

ID  adj.P.Val   P.Value t   B   logFC   miRNA_ID_LIST   SPOT_ID
148000  1.86e-02    5.82e-04    3.47    -0.402958   3.91    hsa-miR-3195


However in the paper the calculated values are far different specially logFC value. What could be the reason for this?

Here are two example of calculations of logFC validated in GEO2R analysis which depends if values are already log2 transformed. During GEOQuery analysis there is calculation to transform where expression set is checked for value distribution and log2 transformation is applied-

ex <- exprs(gset)
qx <- as.numeric(quantile(ex, c(0., 0.25, 0.5, 0.75, 0.99, 1.0), na.rm=T))
LogC <- (qx > 100) ||
(qx-qx > 50 && qx > 0)
if (LogC) { ex[which(ex <= 0)] <- NaN
exprs(gset) <- log2(ex) }


Example 1:

=> Sample Values are already log2 Transformed

n(TumorSamples) = 45
n(ControlSamples) = 46

a = average(TumorSamples) = 9.199053111
b = average(ControlSamples) = 4.988139348

logFC = |a - b| = 4.210914


Example 2: => Sample Values are not log2 transformed

n(TumorSamples) = 2
n(ControlSamples) = 2

a = average(log2(TumorSample1) + log2(TumorSample2) ... ) = (log2(84) + log2(21.8)) / 2 = 5.419287

b = average(log2(ControlSample1) + log2(ControlSample2) ... ) = (log2(624) + log2(665)) / 2 = 9.331306

logFC = |a - b| = 3.91202