I'm doing a differential test for monocle and they show that differentialGeneTest() gives the features that are different between your model but doesn't tell you about which specific genes go up for particular groups. Per there documentation, they state "We could also simply compute summary statistics such as mean or median expression level on a per-CellType basis to see this, which might be handy if we are looking at more than a handful of genes."
This makes sense and I have a calculated normalized expression matrix, my main question is does one normally use all single cells to calculate the mean expression, including the cells that have no detectable level or just expressed cells? So for example, a scenario were condition 1 has 400 total cells and 300 cells express geneA and Condition 2 has 200 total cells and only 50 express geneA. If I'm calculating a FC for geneA do I compare
meanexpression(400 TOTAL cells)/meanexpression(200 TOTAL cells) OR
meanexpression(300 EXPRESSING cells)/mean(50 EXPRESSING cells).
I can see how there would be bias in both and so I wonder which is used in the field?