Threshold determination of strictly standardized mean difference in RNA interference high throughput screening assays

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

RNA interference (RNAi) is a powerful genetic analysis tool for the effficient silencing of target genes and RNAi high throughput screening (HTS) is becoming an important tool in drug discovery and development. The application of RNAi HTS relies on good analytic methods for quality control and hit selection in RNAi HTS experiments. Recently, strictly standardized mean difference (SSMD) has been proposed for measuring the magnitude of difference between two populations. For the use of SSMD in either QC or hit selection, we should determine the threshold of SSMD. To do so, we first present and prove a theorem that establishes the link between SSMD and d+ -probability. Based on the original meaning of SSMD and its probability interpretation, we then propose the cutoff criteria for quality control and hit selection respectively and discuss how to apply these thresholds in RNAi HTS experiments. The link between SSMD and d+-probability and the SSMD thresholds constructed in this paper provide a basis for the use of SSMD in both quality control and hit selection in RNAi HTS experiment.

Original languageEnglish
Title of host publicationIMECS 2007 - International MultiConference of Engineers and Computer Scientists 2007
Pages261-266
Number of pages6
StatePublished - 2007
EventInternational MultiConference of Engineers and Computer Scientists 2007, IMECS 2007 - Kowloon, Hong Kong
Duration: Mar 21 2007Mar 23 2007

Publication series

NameLecture Notes in Engineering and Computer Science
ISSN (Print)2078-0958

Conference

ConferenceInternational MultiConference of Engineers and Computer Scientists 2007, IMECS 2007
Country/TerritoryHong Kong
CityKowloon
Period3/21/073/23/07

Keywords

  • D-probability
  • High throughput screening
  • Hit selection
  • Quality control
  • RNA interference
  • Strictly standardized mean difference

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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