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What is the difference between fold-change and log fold-change?
If you think that fold-change is the ‘expression level’ in one set of samples (set A) divided by the ‘expression level’ in another set (set B), then log-fold-change is the log of that value (typically to base 2).
What does FDR mean in RNA-seq?
false discovery rate
An FDR value is a p-value adjusted for multiple tests (by the Benjamini-Hochberg procedure). It stands for the “false discovery rate” it corrects for multiple testing by giving the proportion of tests above threshold alpha that will be false positives (i.e., detected when the null hypothesis is true).
Why do we use log2 fold change?
Log2 aids in calculating fold change, by which measure the up-regulated vs down-regulated genes between samples. Usually, Log2 measured data more close to the biologically-detectable changes.
What are the uses of log2 fold change?
If we use log2(fold change), fold changes lower than 1 (when B > A) become negative, while those greater than 1 (A > B) become positive. Now the values are symmetrical and it’s easier to see fold changes in both directions on one plot.
Which is the correct fold change for Test status?
Fold change > 1.5, FDR < 0.05, P-value < 0.05 and ‘Test status’ = OK is one criteria which was taken, but I have also seen people considering fold change > 2. I took 3 replicates for the mutant and the wild type each.
Which is the priority for selecting the DEGs?
Say, at FDR 0.05 you expect 20% (correction, 5%) of your genes to be in fact NOT differentially expressed. So filtering on logFC you can arrive to a situation where all your filtered genes are in fact false positives. The best way to deal with this problem to my knowledge is to use the TREAT function from the limma package in Bioconductor.
What’s the difference between p-values and FDRs?
However, p-values (and FDRs) have their own problems- at small p-values, they can be ‘twitchy’ from study to study, and show big swings (e.g, 0.05 in one study, 1E-6 in another), while fold changes, particularly for well-annotated genes with reliable signal intensity/ counts, can be much more stable across studies.
Can a fold change be used to reduce deg?
Filtering at some fold change is something that can be done for reducing the number of deg in case you get a lot, but remember that there is no reason to think that for different genes the larger the fold change imply a larger effect on the downstream processes. It depends on a lot of additional things.
https://www.youtube.com/watch?v=Nm4QY3_5Ts0