Batch effects are sub-groups of measurements that have qualitatively different behaviour across conditions and are unrelated to the biological or scientific variables in a study. For example, batch effects may occur if a subset of experiments was run on Monday and another set on Tuesday, if two technicians were responsible for different subsets of the experiments or if two different lots of reagents, chips or instruments were used.
Methods for removing batch effects
最简单的就是记录实验中时间这个变量，然后对差异表达的基因进行聚类，看是否都和时间相关，如果相关就证明存在batch effect。 同样，如果不同平台的数据之间存在batch effect ，就不能简单的整合。
大家可能都会问标准化，会不会处理掉batch effect ？