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Assessing the validity and reproducibility of genome-scale predictions.


ABSTRACT: Validation and reproducibility of results is a central and pressing issue in genomics. Several recent embarrassing incidents involving the irreproducibility of high-profile studies have illustrated the importance of this issue and the need for rigorous methods for the assessment of reproducibility.Here, we describe an existing statistical model that is very well suited to this problem. We explain its utility for assessing the reproducibility of validation experiments, and apply it to a genome-scale study of adenosine deaminase acting on RNA (ADAR)-mediated RNA editing in Drosophila. We also introduce a statistical method for planning validation experiments that will obtain the tightest reproducibility confidence limits, which, for a fixed total number of experiments, returns the optimal number of replicates for the study.Downloadable software and a web service for both the analysis of data from a reproducibility study and for the optimal design of these studies is provided at http://ccmbweb.ccv.brown.edu/reproducibility.html .

SUBMITTER: Sugden LA 

PROVIDER: S-EPMC3810853 | biostudies-other | 2013 Nov

REPOSITORIES: biostudies-other

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Assessing the validity and reproducibility of genome-scale predictions.

Sugden Lauren A LA   Tackett Michael R MR   Savva Yiannis A YA   Thompson William A WA   Lawrence Charles E CE  

Bioinformatics (Oxford, England) 20130917 22


<h4>Motivation</h4>Validation and reproducibility of results is a central and pressing issue in genomics. Several recent embarrassing incidents involving the irreproducibility of high-profile studies have illustrated the importance of this issue and the need for rigorous methods for the assessment of reproducibility.<h4>Results</h4>Here, we describe an existing statistical model that is very well suited to this problem. We explain its utility for assessing the reproducibility of validation exper  ...[more]

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