Literature DB >> 17517904

A new method with flexible and balanced control of false negatives and false positives for hit selection in RNA interference high-throughput screening assays.

Xiaohua Douglas Zhang1.   

Abstract

The z-score method and its variants for testing mean difference are commonly used for hit selection in high-throughput screening (HTS) assays. Strictly standardized mean difference (SSMD) offers a way to measure and classify the short interfering RNA (siRNA) effects. In this article, based on SSMD, the authors propose a new testing method for hit selection in RNA interference (RNAi) HTS assays. This SSMD-based method allows the differentiation between siRNAs with large and small effects on the assay output and maintains flexible and balanced control of both the false-negative rate, in which the siRNAs with strong effects are not selected as hits, and the restricted false-positive rate, in which the siRNAs with weak or no effects are selected as hits. This method directly addresses the size of siRNA effects represented by the strength of difference between an siRNA and a negative reference, whereas the classic z-score method and t-test of testing no mean difference address whether the mean of an siRNA is exactly the same as the mean of a negative reference. This method can readily control the false-negative rate, whereas it is nontrivial for the classic z-score method and t-test to control the false-negative rate. Therefore, theoretically, the SSMD-based method offers better control of the sizes of siRNA effects and the associated false-positive and false-negative rates than the commonly used z-score method and t-test for hit selection in HTS assays. The SSMD-based method should generally be applicable to any assay in which the end point is a difference in signal compared to a reference sample, including those for RNAi, receptor, enzyme, and cellular function.

Mesh:

Year:  2007        PMID: 17517904     DOI: 10.1177/1087057107300645

Source DB:  PubMed          Journal:  J Biomol Screen        ISSN: 1087-0571


  35 in total

Review 1.  Statistical methods for analysis of high-throughput RNA interference screens.

Authors:  Amanda Birmingham; Laura M Selfors; Thorsten Forster; David Wrobel; Caleb J Kennedy; Emma Shanks; Javier Santoyo-Lopez; Dara J Dunican; Aideen Long; Dermot Kelleher; Queta Smith; Roderick L Beijersbergen; Peter Ghazal; Caroline E Shamu
Journal:  Nat Methods       Date:  2009-08       Impact factor: 28.547

2.  cSSMD: assessing collective activity for addressing off-target effects in genome-scale RNA interference screens.

Authors:  Xiaohua Douglas Zhang; Francesca Santini; Raul Lacson; Shane D Marine; Qian Wu; Luca Benetti; Ruojing Yang; Alex McCampbell; Joel P Berger; Dawn M Toolan; Erica M Stec; Daniel J Holder; Keith A Soper; Joseph F Heyse; Marc Ferrer
Journal:  Bioinformatics       Date:  2011-08-16       Impact factor: 6.937

3.  Defining a standard and weighted mathematical index for maturation of dendritic cells.

Authors:  Abdolamir Landi; Mohammad Tayfeh Aligodarzi; Ali Khodadadi; Lorne A Babiuk; Sylvia van Drunen Littel-van den Hurk
Journal:  Immunology       Date:  2017-11-24       Impact factor: 7.397

4.  Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer.

Authors:  Shameem Fawdar; Eleanor W Trotter; Yaoyong Li; Natalie L Stephenson; Franziska Hanke; Anna A Marusiak; Zoe C Edwards; Sara Ientile; Bohdan Waszkowycz; Crispin J Miller; John Brognard
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-08       Impact factor: 11.205

5.  Use of metal oxide nanoparticle band gap to develop a predictive paradigm for oxidative stress and acute pulmonary inflammation.

Authors:  Haiyuan Zhang; Zhaoxia Ji; Tian Xia; Huan Meng; Cecile Low-Kam; Rong Liu; Suman Pokhrel; Sijie Lin; Xiang Wang; Yu-Pei Liao; Meiying Wang; Linjiang Li; Robert Rallo; Robert Damoiseaux; Donatello Telesca; Lutz Mädler; Yoram Cohen; Jeffrey I Zink; Andre E Nel
Journal:  ACS Nano       Date:  2012-04-24       Impact factor: 15.881

6.  Robust Analysis of High Throughput Screening (HTS) Assay Data.

Authors:  Changwon Lim; Pranab K Sen; Shyamal D Peddada
Journal:  Technometrics       Date:  2013-05-01

7.  Classification NanoSAR development for cytotoxicity of metal oxide nanoparticles.

Authors:  Rong Liu; Robert Rallo; Saji George; Zhaoxia Ji; Sumitra Nair; André E Nel; Yoram Cohen
Journal:  Small       Date:  2011-03-24       Impact factor: 13.281

8.  A Genome-wide RNAi Screen for Microtubule Bundle Formation and Lysosome Motility Regulation in Drosophila S2 Cells.

Authors:  Amber L Jolly; Chi-Hao Luan; Brendon E Dusel; Sara F Dunne; Michael Winding; Vishrut J Dixit; Chloe Robins; Jennifer L Saluk; David J Logan; Anne E Carpenter; Manu Sharma; Deborah Dean; Andrew R Cohen; Vladimir I Gelfand
Journal:  Cell Rep       Date:  2016-01-07       Impact factor: 9.423

9.  Processing pathway dependence of amorphous silica nanoparticle toxicity: colloidal vs pyrolytic.

Authors:  Haiyuan Zhang; Darren R Dunphy; Xingmao Jiang; Huan Meng; Bingbing Sun; Derrick Tarn; Min Xue; Xiang Wang; Sijie Lin; Zhaoxia Ji; Ruibin Li; Fred L Garcia; Jing Yang; Martin L Kirk; Tian Xia; Jeffrey I Zink; Andre Nel; C Jeffrey Brinker
Journal:  J Am Chem Soc       Date:  2012-09-17       Impact factor: 15.419

10.  A lentivirus-mediated genetic screen identifies dihydrofolate reductase (DHFR) as a modulator of beta-catenin/GSK3 signaling.

Authors:  Richard A Klinghoffer; Jason Frazier; James Annis; Jason D Berndt; Brian S Roberts; William T Arthur; Raul Lacson; Xiaohua Douglas Zhang; Marc Ferrer; Randall T Moon; Michele A Cleary
Journal:  PLoS One       Date:  2009-09-03       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.