Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method.
Ying YuNaixin ZhangYuanbang MaiLuyao RenQiaochu ChenZehui CaoQingwang ChenYaqing LiuWanwan HouJingcheng YangHuixiao HongJoshua XuWeida TongLianhua DongLeming ShiXiang FangYuanting ZhengPublished in: Genome biology (2023)
Multiomics measurements are prone to batch effects, which can be effectively corrected using ratio-based scaling of the multiomics data. Our study lays the foundation for eliminating batch effects at a ratio scale.