Edge effect detection for real-time cellular analyzer using statistical analysis

Abstract

Real time cellular analyzers (RTCA) are widely used to test the cytotoxicity of chemicals. However, there are some uncontrollable factors, which are detrimental to the experimental quality. One of the fundamental issues is the edge effect. Abnormal time-dependent cellular response curves (TCRCs) are observed when the wells are located at the edge of the E-plate. In this paper, the Smirnov test was used to detect the edge effect. The average normalized cell index (NCI) of the negative control located in the inner wells was taken as the standard. Thereafter, all TCRCs were divided into several intervals, and their corresponding empirical distribution functions (EDFs) of the mean NCI and NCI located at the edge wells were calculated, and hypothesis testing was used to determine the differences of the EDFs. The experimental results evaluated the performance of the proposed algorithm. This framework provided a systematic method for edge-effect detection.