Title: A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays.
Authors: Hsieh, Jui-Hua; Sedykh, Alexander; Huang, Ruili; Xia, Menghang; Tice, Raymond R
Published In J Biomol Screen, (2015 Aug)
Abstract: A main goal of the U.S. Tox21 program is to profile a 10K-compound library for activity against a panel of stress-related and nuclear receptor signaling pathway assays using a quantitative high-throughput screening (qHTS) approach. However, assay artifacts, including nonreproducible signals and assay interference (e.g., autofluorescence), complicate compound activity interpretation. To address these issues, we have developed a data analysis pipeline that includes an updated signal noise-filtering/curation protocol and an assay interference flagging system. To better characterize various types of signals, we adopted a weighted version of the area under the curve (wAUC) to quantify the amount of activity across the tested concentration range in combination with the assay-dependent point-of-departure (POD) concentration. Based on the 32 Tox21 qHTS assays analyzed, we demonstrate that signal profiling using wAUC affords the best reproducibility (Pearson's r = 0.91) in comparison with the POD (0.82) only or the AC(50) (i.e., half-maximal activity concentration, 0.81). Among the activity artifacts characterized, cytotoxicity is the major confounding factor; on average, about 8% of Tox21 compounds are affected, whereas autofluorescence affects less than 0.5%. To facilitate data evaluation, we implemented two graphical user interface applications, allowing users to rapidly evaluate the in vitro activity of Tox21 compounds.
PubMed ID: 25904095
MeSH Terms: Artifacts*; Data Interpretation, Statistical; Drug Discovery/methods*; Drug Discovery/standards*; High-Throughput Screening Assays/methods*; High-Throughput Screening Assays/standards*; Humans; Reproducibility of Results; Signal-To-Noise Ratio; Small Molecule Libraries; United States