High throughput screening(HTS)is a widely used effective approach in genome-wide association and large scale protein expression studies,drug discovery,and biomedical imaging research.How to accurately identify candidate ’targets’ or biologically meaningful features with a high degree of confidence has led to extensive statistical research in an effort to minimize both false-positive and false-negative rates.A large body of literature on this topic with in-depth statistical contents is available.We examine currently available statistical methods on HTS and aim to summarize some selected methods into a concise,easy-tofollow introduction for experimental biologists.