4 weeks ago by

United States

The formula is the mean of one group minus the mean of the other. As an example

```
> set.seed(0xabeef)
> dat <- matrix(rnorm(600), 100)
> design <- model.matrix(~gl(2,3))
> topTable(eBayes(lmFit(dat, design)), sort.by = "none")
Removing intercept from test coefficients
logFC AveExpr t P.Value adj.P.Val B
1 -0.4491747 0.17399287 -0.5429128 0.5874922134 0.89526118 -6.04808633
2 0.3470947 -0.01715336 0.4195298 0.6750542325 0.92838912 -6.10501274
3 0.6185414 0.05340375 0.7476245 0.4551259542 0.87194966 -5.92143882
4 -0.1563895 0.32075711 -0.1890264 0.8501680185 0.93595218 -6.17225795
5 1.8959091 -0.65304549 2.2915656 0.0224496919 0.56124230 -3.67201123
6 -2.9805834 0.18930152 -3.6026002 0.0003547357 0.03547357 0.03240607
7 -1.1050169 0.11255957 -1.3356225 0.1824321732 0.86602296 -5.33421999
8 -0.2232205 -0.24504755 -0.2698043 0.7874499872 0.93595218 -6.15449037
9 -0.2715671 0.26674769 -0.3282403 0.7429017243 0.92838912 -6.13773717
10 0.2775211 0.64482350 0.3354369 0.7374713950 0.92838912 -6.13544753
> head(rowMeans(dat[,4:6]) - rowMeans(dat[,1:3]),10)
[1] -0.4491747 0.3470947 0.6185414 -0.1563895 1.8959091 -2.9805834
[7] -1.1050169 -0.2232205 -0.2715671 0.2775211
```