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Abstract:
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High throughput screening (HTS) plays a central role in modern drug discovery, allowing the rapid screening of diverse chemical compounds (i.e., small molecule) or short interfering RNAs (siRNAs) to identify active compounds or effective siRNAs ("hits"). For example, small molecule HTS allows for screening of more than 100,000 compounds a day per screen. Thus, HTS experiments generate a huge amount of data. In order to use these data to identify the most active compounds or effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods for quality control (QC) and hit selection. Here, I present some simple statistical parameters and explore their uses in both quality control and hit selection in RNAi HTS assays.
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