methods to remove variation of individuals in high-throughput experiments

Question

[Zhilong Jia]

In an experiment, the cell from 3 individuals is used for combating with a virus with only one replicate. In other words, there are one treatment and one control group from each cell. Totally, there are 3 treatment and 3 control groups regardless the cell source. However, I've found large variation of individuals. When grouping the data, the data from same individual will group together. So how to remove this variation of individuals? Does the sva package works for this situation? Thank you.

Answer 1

[Devon Ryan]

Just use individual in your design, so ~individual+treatment. Then you've accounted for the inter-individual variance and can simply test the treatment effect.