The Annals of Applied Statistics

A Bayesian measurement error model for two-channel cell-based RNAi data with replicates

Chung-Hsing Chen, Wen-Chi Su, Chih-Yu Chen, Jing-Ying Huang, Fang-Yu Tsai, Wen-Chang Wang, Chao A. Hsiung, King-Song Jeng, and I-Shou Chang

Full-text: Open access

Abstract

RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in human cells can be conducted to identify unknown genes involved in a biological pathway. One challenge researchers face is how to deal with the multiple testing issue and the related false positive rate (FDR) and false negative rate (FNR). This paper proposes a Bayesian hierarchical measurement error model for the analysis of data from a two-channel RNAi high-throughput experiment with replicates, in which both the activity of a particular biological pathway and cell viability are monitored and the goal is to identify short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting cell activity. Simulation studies demonstrate the flexibility and robustness of the Bayesian method and the benefits of having replicates in the experiment. This method is illustrated through analyzing the data from a RNAi high-throughput screening that searches for cellular factors affecting HCV replication without affecting cell viability; comparisons of the results from this HCV study and some of those reported in the literature are included.

Article information

Source
Ann. Appl. Stat., Volume 6, Number 1 (2012), 356-382.

Dates
First available in Project Euclid: 6 March 2012

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1331043400

Digital Object Identifier
doi:10.1214/11-AOAS496

Mathematical Reviews number (MathSciNet)
MR2951541

Zentralblatt MATH identifier
1235.62027

Keywords
Bayesian hierarchical models HCV replication high-throughput screening multiple hypothesis tests RNA interference viral-host interactions

Citation

Chen, Chung-Hsing; Su, Wen-Chi; Chen, Chih-Yu; Huang, Jing-Ying; Tsai, Fang-Yu; Wang, Wen-Chang; Hsiung, Chao A.; Jeng, King-Song; Chang, I-Shou. A Bayesian measurement error model for two-channel cell-based RNAi data with replicates. Ann. Appl. Stat. 6 (2012), no. 1, 356--382. doi:10.1214/11-AOAS496. https://projecteuclid.org/euclid.aoas/1331043400


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Supplemental materials

  • Supplementary material: A Computer algorithm for analyzing data from two-channel cell-based RNAi experiments with replicates. This note provides the hybrid MCMC algorithm for sampling the posterior distribution used in Chen et al. (2011) and several observations used in designing this algorithm so as to make it more efficient.