2007
DOI: 10.1038/nmeth1089
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A probability-based approach for the analysis of large-scale RNAi screens

Abstract: We describe a statistical analysis methodology designed to minimize the impact of off-target activities upon large-scale RNA interference (RNAi) screens in mammalian cells. Application of this approach enhances reconfirmation rates and facilitates the experimental validation of new gene activities through the probability-based identification of multiple distinct and active small interfering RNAs (siRNAs) targeting the same gene. We further extend this approach to establish that the optimal redundancy for effic… Show more

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Cited by 329 publications
(370 citation statements)
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“…S1B and Methods and Dataset S2 for a detailed description of these calculations). In addition to scoring the individual shRNAs, we derived gene level calls from the 17 shRNAs for each gene by applying the Redundant siRNA Activity (RSA) algorithm, which calculates gene-centric P values (23). To identify genes whose product is selectively required for growth in a subset of cancer lines, we performed k-means clustering (24) of the RSA value for each gene to define groups of "sensitive" and "insensitive" cell lines and subsequently ranked hits based on the difference in cluster centers (SI Appendix, Methods).…”
Section: Resultsmentioning
confidence: 99%
“…S1B and Methods and Dataset S2 for a detailed description of these calculations). In addition to scoring the individual shRNAs, we derived gene level calls from the 17 shRNAs for each gene by applying the Redundant siRNA Activity (RSA) algorithm, which calculates gene-centric P values (23). To identify genes whose product is selectively required for growth in a subset of cancer lines, we performed k-means clustering (24) of the RSA value for each gene to define groups of "sensitive" and "insensitive" cell lines and subsequently ranked hits based on the difference in cluster centers (SI Appendix, Methods).…”
Section: Resultsmentioning
confidence: 99%
“…This screen, previously developed in our laboratory, already led to the discovery of a new role for BRCA2 and PALB2 in checkpoint signalling 14 . Data from the screen were statistically analysed to identify candidate genes 15 ( Supplementary Fig. 1a-c).…”
Section: Resultsmentioning
confidence: 99%
“…The data obtained from the screen was submitted to a redundant siRNA activity analysis that models the probability of a gene 'hit' based on the collective activities of multiple siRNAs per gene 15 . Using this method, the siRNAs were ranked according to their score.…”
Section: Methodsmentioning
confidence: 99%
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“…Hits were identified as those with a median IC 50 shift of median IC 50 AE 3MAD (median absolute deviations) or greater (11,12). To assign statistical significance to siRNA hits identified from the siRNA screen, we then modeled the collective activities of the 4 individual siRNAs used for each gene by using redundant siRNA activity (RSA) analysis (13). Briefly, the normalized, log 2 transformed IC 50 shifts of all siRNAs were rank ordered and the rank distribution of all siRNAs targeting the same gene was examined and a P value was calculated on the basis of an iterative hypergeometric distribution formula (13).…”
Section: Hit Identification and Statistical Analysismentioning
confidence: 99%