A New Workflow Automating Data Analysis in Gene Expression Screens Across Assay Formats Produces Consistent Results at Scale and Efficiency
ELRIG Drug Discovery, Liverpool, UK
October 19, 2021
The characterization of gene expression changes has broad applications, including (1) screening of RNA-based or small molecule drugs which function by direct modulation of gene expression, e.g., by altering pre-mRNA splicing, (2) verifying effects of protein-targeting drugs on given cellular pathways, and (3) toxicity profiling or assessing target selectivity. Today, assays such as multiplexed reverse transcription qPCR (RT-qPCR) or bead-based technologies like the QuantiGeneTM assay can be performed on automated platforms to enable screening of gene expression at scale. These technologies allow a large increase in throughput, but to date, there exists no shared analysis workflow which can consistently and efficiently process high-volume data for all gene expression assays. In this poster, we present a new, highly automated workflow in Genedata Screener which enables major efficiency gains and standardized, high-quality results. This workflow provides built-in functionality for core processing and quality control (QC) steps common to all gene expression assays, such as: normalization to house-keeping genes, which can be flexibly assigned by the user; a dose-response curve fit method purpose-built for Fold Change measurements, with configurable parameter restriction and result validity rules; automatic QC, including masking of unreliable measurements and flagging of cytotoxic compounds, and dedicated QC plots. Additionally, the workflow contains technology-specific features, such as the ability to view raw amplification curves for RT-qPCR experiments and robust, automated determination of Ct values. Recently, this workflow was deployed at Evotec to streamline RT-qPCR-based screens from compound logistics to one-click reporting of results, significantly shortening cycle times.