Poster Open Access
Cuklina, Jelena; Lee, Chloe; Williams, Evan G.; Sajic, Tatjana; Collins, Ben; Rodriguez-Martinez, Maria; Pedrioli, Patrick; Aebersold, Ruedi
In large-scale proteomic studies, logistics restrict the sample number that can be processed in one batch. This inevitably leads to systematic technical bias, known as batch effects. In this study, we analyse batch effects in proteomics. We test existing batch correction tools for their suitability in proteomic studies and introduce new methods for correction and quality control.