12 months ago

WCIP | Glasgow | UK

Granted that with just one data-point you can't do much without making further assumptions. It seems to me that you want to know how *extreme* your log-fold change is. For this, you could make a guess, more or less driven by data you have, about the distribution of log-fold changes from which your data-point comes from. Then, you can ask where your log-fold-change maps on this distribution. For example, if you assume the distribution is normally distributed with mean 0 and standard deviation 2, then (in R) `pnorm(q, mean= 0, sd= 2)`

tells you how extreme your data point q is. For example:

```
pnorm(q= 2.5, mean= 0, sd= 2) # 0.89, not very close to 0 or 1, not very extreme
pnorm(q= 5, mean= 0, sd= 2) # 0.99, quite extreme
pnorm(q= 5, mean= 0, sd= 5) # 0.84, not very extreme anymore
```

Do you have the SE of the fold-change? You can't calculate the p-value from only a fold-change, you'll need some other value to let you know how confident that estimate is.

To the best of my knowledge, this is not possible with just the fold change.