good "benchmark" or minimum bayes factor for differential expression?
I'm filtering a file with genome wide analysis of bayes factors between two stages in neuron development. What's a good minimum BF for a gene to be counted as differentially expressed? In a Nature Communications paper it seems that they used BF>20, but I'm not sure if that's just for the specific study they were doing, or if that's a generally universal value.
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In general, Bayes Factors are a bit like interpreting a p-value and the choice of cutoff for "significance" is arbitrary. The Jeffrey's scale is one widely used suggested scaling of significance where K's >10 are "strong" inidcators of significant differences, and K's > 10^2 are "decisive" indicators of significance and anything in between as "very strong" indication (that is, that gene expression levels for population M2 are greater than those for population M1, for example).
In my experience, Bayes factors are not at all commonly used for differential gene expression, so you may need to convince an audience of the validity of the methods used to generate that file (not to mention explaining just what a Bayes factor is as most genomic biologists will have never heard of the term).Last edited by mbblack; 08-05-2015, 04:18 AM.Michael Black, Ph.D.
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