Oh so I guess you must have R3.1 and later to get the newest DESeq2? Since I've installed the package very recently but I did have R 3.0.1..
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hi apredeus, I'm note exactly sure why it would have changed so much between 1.2 and 1.4, as there were only slight changes to the gene-wise dispersion estimation routine, but I can say that the code base has stabilized since last fall. Bioc users are always 6 months behind the development cycle, which means that bugs/changes that users request in October have to wait until March to be released.
The other thing is that p-values are tail probabilities, which means they are very sensitive to slight changes in model parameters.
For example, say we have some Z scores:
> set.seed(1)
> z <- rnorm(10000,0,7)
Then we make and adjust p-value according to two models of the data:
> table(p.adjust(2*pnorm(abs(z),0,5,lower=FALSE),method="BH") < .1)
FALSE TRUE
9507 493
> table(p.adjust(2*pnorm(abs(z),0,5.25,lower=FALSE),method="BH") < .1)
FALSE TRUE
9741 259
So a 5% change in a model parameter translates to a nearly halving of adjusted p-values less than 0.1.
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Michael, Simon:
would it be possible to output two mean expression columns (conditions 1 and 2) instead of only one in the results table? It would be a lot more informative I think. You can simply glance at it and tell if there are some dramatic changes.
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Originally posted by apredeus View PostMichael, Simon:
would it be possible to output two mean expression columns (conditions 1 and 2) instead of only one in the results table? It would be a lot more informative I think. You can simply glance at it and tell if there are some dramatic changes.
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