Understanding the output of Negative Binomial in DESeq2

Are zero is a default option of log2fold change to be considered as up and down?

Yes, by default, the null hypothesis is that the log2FoldChange is zero.

Does this mean that there are seven genes in total that will have significant adjusted p-value?

Yes, you are interpreting your results correctly that you have 7 genes in total where the log2FoldChange is significantly different from 0.

i recall when multiple linear regression is fitted, we get an overall p-value so we can quickly know whether at least one coefficient is not equal to zero if p-value <0.05 or vice versa or I can just skim through the output to examine how many coefficients are significant.

This sort of depends on how you have set the design in DESeq2. In a basic differential expression analysis, where you just have 2 groups that you wish to compare, DESeq2 will fit 36,955 independent negative binomial models each with only a single coefficient (actaully, two coefficients, including the interscept). The p-value that is reported for each gene is the p-value for the null hypothesis that the value of that single coefficient for that gene.

If your design includes more than one experimental factor, or you have an experimental factor that has more than two levels, you will end up with 36,955 negative binomial models with more than 1 coeffficient. If you are using the wald test, then there is no overall p-value. Instead, the p-value that is reported is determined by the value you give either for coef, contrast or name in your call to results. You can find valid values for the name parameter by running resultNames on your DESeq object.

If you specifically want an overall p-value (say you have three different treatments, and you want to know if treatments, overall, have any effect), then you need to use the Liklihood Ratio Test rather than the wald test. See bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#likelihood-ratio-test

However, I am wondering whether all genes used for visialization in volcano plot?

I don’t know EnhancedVolcano inside out, but I believe it does plot all genes. It looks like it has two few points because so many points are in the same place.

Read more here: Source link