High-Throughput RNA Interference Screening: Tricks of the Trade
| Autor: | Mary-Ann Bjornsti, N. Miranda Nebane, Russell Sheppard, Sara McKellip, Melinda Sosa, Kanupriya Whig, Tatjana Coric, Lynn Rasmussen, LaKeisha Woods, E. Lucile White |
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| Rok vydání: | 2013 |
| Předmět: |
Coefficient of variation
Reproducibility of Results Microfluidic Analytical Techniques Article Standard deviation High-Throughput Screening Assays Computer Science Applications Medical Laboratory Technology HEK293 Cells Statistics Animals Humans RNA Interference Genetic Testing RNA Small Interfering Throughput (business) Simulation Mathematics |
| Zdroj: | SLAS Technology. 18:334-339 |
| ISSN: | 2472-6303 |
| DOI: | 10.1177/2211068213486786 |
| Popis: | The process of validating an assay for high-throughput screening (HTS) involves identifying sources of variability and developing procedures that minimize the variability at each step in the protocol. The goal is to produce a robust and reproducible assay with good metrics. In all good cell-based assays, this means coefficient of variation (CV) values of less than 10% and a signal window of fivefold or greater. HTS assays are usually evaluated using Z′ factor, which incorporates both standard deviation and signal window. A Z′ factor value of 0.5 or higher is acceptable for HTS. We used a standard HTS validation procedure in developing small interfering RNA (siRNA) screening technology at the HTS center at Southern Research. Initially, our assay performance was similar to published screens, with CV values greater than 10% and Z′ factor values of 0.51 ± 0.16 (average ± standard deviation). After optimizing the siRNA assay, we got CV values averaging 7.2% and a robust Z′ factor value of 0.78 ± 0.06 (average ± standard deviation). We present an overview of the problems encountered in developing this whole-genome siRNA screening program at Southern Research and how equipment optimization led to improved data quality. |
| Databáze: | OpenAIRE |
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