I'm working with a genomic data-set with ~31k end-points and have performed an F-test across 5 groups for each end-point. The QA measurments on the individual micro-arrays all look good. One of the first things I do in my work-flow is take a look at the p-valued distribution. it is my understanding that, if the findings are due to chance alone, the p-value distribution should be uniform. In this case the histogram, even with 1000 break points, starts low on the left and climbs almost linearly to the right. In other words, very skewed towards high p-values. I understand that this could be happening by chance alone, but the same behavior is seen in the two contrasts of interest I looked at and I have seen it in a couple of our other genomic, high-dimensional experiments as well. I might also add that I looked at the actual numbers of genes with p-val < X and indeed, for each X < 0.05, there are far fewer sig. genes than one would expect by chance.
I can't figure out what is causing this and, if there is a cause, I'd like to be able to tell the experimenter if it indicates a technical factor. I've had other experiments where the p-value dist approximates normal and of course those that have nice spikes at low p-values indicating we have some significant genes. I'm addressing this hear rather than to BioC because I suspect there is some basis statistical mechanism that could explain this. Is there? Mark -- Mark W. Kimpel MD ** Neuroinformatics ** Dept. of Psychiatry Indiana University School of Medicine 15032 Hunter Court, Westfield, IN 46074 (317) 490-5129 Work, & Mobile & VoiceMail (317) 663-0513 Home (no voice mail please) ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
