Analysis of variability in high throughput screening data: applications to melanoma cell lines and drug responses
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Kuan-Fu Ding1,2, Darren Finlay4, Hongwei Yin3, William P.D. Hendricks3, Chris Sereduk3, Jeffrey Kiefer3, Aleksandar Sekulic3, Patricia M. LoRusso5, Kristiina Vuori4, Jeffrey M. Trent3, Nicholas J. Schork1,2,3
1J. Craig Venter Institute, La Jolla, San Diego, CA, USA
2University of California, San Diego, CA, USA
3The Translational Genomics Research Institute, Phoenix, AZ, USA
4 Sanford Burnham Prebys Medical Discovery Institute, La Jolla, San Diego, CA, USA
5Yale University, New Haven, CT, USA
Nicholas J. Schork, email: email@example.com
Keywords: melanoma, high-throughput screening, drug screens, computational modeling, variability
Received: July 14, 2016 Accepted: January 27, 2017 Published: February 15, 2017
High-throughput screening (HTS) strategies and protocols have undergone significant development in the last decade. It is now possible to screen hundreds of thousands of compounds, each exploring multiple biological phenotypes and parameters, against various cell lines or model systems in a single setting. However, given the vast amount of data such studies generate, the fact that they use multiple reagents, and are often technician-intensive, questions have been raised about the variability, reliability and reproducibility of HTS results. Assessments of the impact of the multiple factors in HTS studies could arguably lead to more compelling insights into the robustness of the results of a particular screen, as well as the overall quality of the study. We leveraged classical, yet highly flexible, analysis of variance (ANOVA)-based linear models to explore how different factors contribute to the variation observed in a screening study of four different melanoma cell lines and 120 drugs over nine dosages studied in two independent academic laboratories. We find that factors such as plate effects, appropriate dosing ranges, and to a lesser extent, the laboratory performing the screen, are significant predictors of variation in drug responses across the cell lines. Further, we show that when sources of variation are quantified and controlled for, they contextualize claims of inconsistencies and reveal the overall quality of the HTS studies performed at each participating laboratory. In the context of the broader screening study, we show that our analysis can also elucidate the robust effects of drugs, even those within specific cell lines.
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