Hope you all are doing great. I am very new to RNASeq and DESeq2. I know that the negative Binomial (Gamma Poisson) is used to fit this RNAseq count data. All genes are assessed/fitted between two conditions and we get the basemean and log2fold change and then wald test is used to examine whether the coefficient is equal to zero if I am not wrong to determine whether the log2fold change is significant. I am so far familiar with linear rather than generalized linear model. I did a bit of poisson regression before.
I have the attached the output of the model after fitting through DESeq2. In my output, there were five genes are upregulated and 2 genes are downregulated. Are zero is a default option of log2fold change to be considered as up and down?
Does this mean that there are seven genes in total that will have significant adjusted p-value? 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. However, with the negative 2 binomial in DESeq2, I could not find the overall p-value at all
Also, the output could not list all the genes and adjusted p-value there because there are many of them have been fitted. Therefore, I am wondering how could I know which genes have significant log2fold change by looking through the output? Hope you do not mind me with my question as I am very new to RNAseq experiment and the analysis.
Additonally, I understand how to interpret the volcano plot. However, I am wondering whether all genes used for visialization in volcano plot? I have attached the plot, it seems not many dot points there so I am assuming only some genes are used to constructed volocano plot. Am I right? Do you think the plot looks alright. Sorry for asking and looking forward to hearing from author and seniors at your earliest convenience.