Hi All,

We performed the RNA seq with below design. We have: (A) containing a number of strains with mutation A and (B) containing a number of strain with mutation B.

We performed two experiments of cell-model infection. The 1st experiment was done with half of strains from A and half of strains from B. The 2nd experiment was performed later with the rest of strains from A and B. Both experiments used the same cell line and included uninfected cells. RNA from both experiments were sequenced at one time. We want to compare RNA seq of cells infected with all strains A vs. cells infected with all strains B

We need to combine the data from the two experiments. When we plotted PCA, we saw two distinguished clusters for A and B. The uninfected cells from experiment 1 and 2 also seperated far way in the PCA plot, indicating the batch effect. The question is that should we perform ComBat to remove the batch effect in this kind of design. Or any methods that can help us to be able to combine the data from these two experiments for further analysis between A vs.B?.

Many thanks,

It appears that batch is orthogonal to the treatment, so you can just fit a batch effect in your model.

ComBat is appropriate for this type of design and BatchQC can be used to evaluate how well ComBat corrects for the batch effect. BatchQC provides a shiny interface where you can normalize, batch correct and view multiple visualization to determine the effectiveness of batch effect correction. Your batch-corrected (and/or normalized) data can then be exported for downstream use.