Hello guys,

It may seem like a basic question, but this is causing confusion.

What is the difference between fold change and Log fold change?

Regards,

I find pictures helpful when thinking about these concepts, so quickly made some visualizations for you. They expand on WouterDeCoster's and h.mon's comments. The figures were made in R using with the following code:

    #Generate fake data    
    fake <- data.frame("gene" = as.numeric(c(1:50)), "pre" = as.numeric(seq(1,99,2)), "post"= as.numeric(seq(99,1,-2)))
    #Calculate fold change
    fake$fold <- fake$post/fake$pre
    #Calculate log2 fold change
    fake$logfold <- log2(fake$fold)
    #Visualize
    library(ggplot2)
    ggplot(fake, aes(x = gene, y = fold)) + geom_line()
    ggplot(fake, aes(x = gene, y = logfold)) + geom_line() + ylab("Log2(FC)")

Let's say you have 50 genes (for the sake of convenience, the genes are called "1", "2", "3", ... , "50") and you measure expression before and after some type of treatment. You then measure the fold change of the genes due to treatment: FC = expression(post) / expression(pre). As russhh indicated, the logFC is simply log2(FC). 

In this dataset, half the genes were upregulated and the other half downregulated. Interpreting the untransformed fold change is tricky: here it looks like gene1 had a huge fold change, close to 100, but what about genes30-50? It's hard to tell what their value is, and also by how much they differ from each other.

![enter image description here][1]

Performing the log2 transformation scales the data and facilitates the interpretation, as illustrated below.

![enter image description here][2]

The differences in expression in genes30-50 are now much more obvious.

  [1]: https://i.imgur.com/dD7RC7n.png
  [2]: https://i.imgur.com/5GywhTT.png