Abstract: High-throughput data are usually a product of long and complex experiments in laboratories or fields. Due to the multi-step process when generating data, a concern for possible contamination in high-dimensional data is naturally more severe than low-dimensional counterparts. We propose a new two-stage procedure for detecting multiple outliers when the dimension of the data is much...