[BioC] P values on Log or Non-Log Values

[James MacDonald]

>From a theoretical standpoint it is more correct to do t-tests on logged data because one of the assumptions of the t-test is that the underlying data are normally distributed. Microarray expression values are almost always strongly right-skewed, and logging causes the distribution to become much more symmetrical.

It is doubtful that the logged data are normally distributed, but the t-test is fairly robust to violations of the normality assumption as long as the data are relatively symmetrical.

You can also permute your data to estimate the null distribution if you want to remove the reliance on normality. However, in my opinion it is still better to use symmetrical (logged) data when permuting.

HTH,

Jim


James W. MacDonald
UMCCC Microarray Core Facility
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

>>> "Park, Richard" <Richard.Park at joslin.harvard.edu> 05/05/03 10:34AM >>>
Hi Everyone, 
I am currently using the mt.teststat to calculate p-values between various samples. I was wondering if anyone knew if it was ok to run p-values on logged or non-logged values? In the past using MAS processing, I always calculated pvalues on the raw values, however I have recently switched to processing cel files through rma and the raw data produced from this processing is log base 2. 
 
My lab has noticed that log transformation Is not very visible with high p.values (above 0.1), but spreads them all over the place in the low (significant !) range. By running a t.test on loged values, it greatly enhances the significance (up to 100-fold, compared to running on straight values) when significance derives from tight distributions, but has very little or no effect when significance derives from more distant means
 
Anyone have any ideas on which method is correct? 
 
thanks, 
Richard Park 
Computational Data Analyzer
Joslin Diabetes Center

_______________________________________________
Bioconductor mailing list
Bioconductor at stat.math.ethz.ch 
https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor