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False negative rates in Drosophila cell-based RNAi screens: a case study

Authors: Booker, Matthew; Samsonova, Anastasia; Kwon, Young; Flockhart, Ian; Mohr, Stephanie; Perrimon, Norbert;

False negative rates in Drosophila cell-based RNAi screens: a case study

Abstract

Abstract Background High-throughput screening using RNAi is a powerful gene discovery method but is often complicated by false positive and false negative results. Whereas false positive results associated with RNAi reagents has been a matter of extensive study, the issue of false negatives has received less attention. Results We performed a meta-analysis of several genome-wide, cell-based Drosophila RNAi screens, together with a more focused RNAi screen, and conclude that the rate of false negative results is at least 8%. Further, we demonstrate how knowledge of the cell transcriptome can be used to resolve ambiguous results and how the number of false negative results can be reduced by using multiple, independently-tested RNAi reagents per gene. Conclusions RNAi reagents that target the same gene do not always yield consistent results due to false positives and weak or ineffective reagents. False positive results can be partially minimized by filtering with transcriptome data. RNAi libraries with multiple reagents per gene also reduce false positive and false negative outcomes when inconsistent results are disambiguated carefully.

Related Organizations
Keywords

Proteasome Endopeptidase Complex, Gene Expression Profiling, Research Subject Categories::NATURAL SCIENCES::Biology::Other biology::Functional genomics, 610, QH426-470, 004, Genetics, Animals, Cluster Analysis, Drosophila, RNA Interference, Ribosomes, TP248.13-248.65, Biotechnology, Research Article, RNA, Double-Stranded

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
45
Top 10%
Top 10%
Top 10%
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gold