I have some questions regarding RNAseq analysis.
My experimental design is 1 factor (fish exposed to one compounds) with 4 levels (control and 3 different doses). We are interested to compare not only the control with each single dose or to all doses at the same time, but also see if there is a dose-response effect. For that reason we are not as interested on comparisons two-by two, but more in multiple comparison test (such as tukey post hoc after doing a ONE-Way ANOVA).
From what I understand we can use the likelihood ratio test, which compares two models: one in which the expression stays flat, and another in which the expression changes over doses (at any or all doses). The likelihood ratio test will be done ~condition vs ~1, for the "full" and "reduced" formula.
My questions now are:
1. Why ~1 is asigned for the "reduced" formula? (this is completely ignorance)
2. Once the likelihood ratio test is done, will this give me an outcome with a list of genes and significant levels only (as a regular ANOVA will do) or can I also extract where those differences are located (so like a post hoc test). Ideally I would like to be able to give significances (at least from the genes that are significantly different) as the following example: Control (a), Dose 1 (a), Dose 2 (ab), Dose 3 (b).