I have two questions about my RNA-Seq datasets that I have analyzed using Deseq2. I have used PCA plots for exploratory purposes. Out of the two groups (each group has 3 biological replicates) compared, samples of one group are spread apart on the plot and its really hard to decide which of the samples should be removed as outlier to proceed to differential expression analysis.
1. What is the acceptable % of variance to make an outlier decision. I was thinking if there is any way I could plot samples of one group separately at a time, variance would be more clear and easy to identify the outlier? Is there any way I could do this?
2. For an other dataset, where I have 5 biological replicates for each group (and als control Vs. treatment between two cell types). I see similar clustering pattern for some samples within a group as described above. Since PCA plot shows two dimensions and suitable for showing differences between two groups/conditions, Is there anyway, I could plot more than two groups at a time and see how/where samples cluster on the plot?