I am having a problem with batch effects on my RNA sequencing data, where I try to determine differential expression. I do have 3 experimental groups and a control group (4 samples each). In the first batch where 2 samples of the control and two of samples of two experimental groups (6 samples). In the second batch where two top up sample for each group from the first run and 4 samples of a additional experimental group (10 samples). Unfortunately I am having not much clue of bioinformatics. I did use galaxy dashboard, made a count matrix with all 16 samples, used it as input for differential expression analysis and ran edge R, DESeq2 and Voom. Is there a way of using galaxy dashboard to reduce the batch effect I am experiencing?
Thaank you, Lena