Evaluation of Type 1 Error Rates in Duplex Sequencing for Mutagenicity Testing using Vehicle Control Data and Simulation Analyses

Evaluation of Type 1 Error Rates in Duplex Sequencing for Mutagenicity Testing using Vehicle Control Data and Simulation Analyses | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Environmental and Molecular Mutagenesis This is a preprint and has not been peer reviewed. Data may be preliminary. 14 November 2025 V1 Latest version Share on Evaluation of Type 1 Error Rates in Duplex Sequencing for Mutagenicity Testing using Vehicle Control Data and Simulation Analyses Authors : Andrew Williams 0000-0002-7637-7686 [email protected] , Shaofei Zhang 0000-0003-0169-4078 , Dingzhou Li , Xiaowen Sun , Maik Schuler J , Francesco Marchetti , and Carole Yauk Authors Info & Affiliations https://doi.org/10.22541/au.176312890.01167435/v1 222 views 142 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Accurate mutation detection and quantification are crucial for understanding mutagenesis and its potential health implications. Traditional in vivo mutagenicity assays, such as the transgenic rodent gene mutation assay, are limited by their focus on single reporter genes and inability to efficiently generate mutation spectra. Error-corrected sequencing (ECS) technologies like Duplex Sequencing (DS) offer significant advantages, including extremely low error rates and ability to measure mutation frequencies (MFs) across various tissues and model organisms. Before DS can be adopted for regulatory purposes, its performance characteristics, particularly the type 1 error rate must be rigorously established. We evaluated the type 1 error rate of DS through empirical analysis of vehicle control data and complementary simulation studies. Using 138 control mouse liver samples from 28 studies analyzed with the TwinStrand Mouse Mutagenesis Panel, we performed variance component analysis and found that experiment-level variability exceeds within-experiment sample variability. To evaluate the impact of between-study heterogeneity, we simulated overdispersed binomial data informed by the observed variance components. Removing the most variable studies reduced overdispersion and improved control of the type 1 error rate. Our findings demonstrate that DS maintains appropriate type 1 error rates (~0.05) when study heterogeneity is limited and at least four samples per group are used. Under greater overdispersion, sample sizes of five or six per group may be needed to achieve comparable control of the type 1 error rate. These results underscore the importance of combining empirical and simulation-based approaches to evaluate and optimize the statistical performance of emerging genomic technologies. Supplementary Material File (figures final.pptx) Download 410.23 KB File (williams_final_submission.docx) Download 343.63 KB Information & Authors Information Version history V1 Version 1 14 November 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Environmental and Molecular Mutagenesis Keywords error-corrected sequencing historical controls simulation analysis type 1 error rate Authors Affiliations Andrew Williams 0000-0002-7637-7686 [email protected] Health Canada Healthy Environments and Consumer Safety Branch View all articles by this author Shaofei Zhang 0000-0003-0169-4078 Pfizer Global Research and Development View all articles by this author Dingzhou Li Pfizer Global Research and Development View all articles by this author Xiaowen Sun Pfizer Global Research and Development View all articles by this author Maik Schuler J Bristol-Myers Squibb Co Research & Development New Brunswick View all articles by this author Francesco Marchetti Health Canada Healthy Environments and Consumer Safety Branch View all articles by this author Carole Yauk University of Ottawa Department of Biology View all articles by this author Metrics & Citations Metrics Article Usage 222 views 142 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Andrew Williams, Shaofei Zhang, Dingzhou Li, et al. Evaluation of Type 1 Error Rates in Duplex Sequencing for Mutagenicity Testing using Vehicle Control Data and Simulation Analyses. Authorea . 14 November 2025. DOI: https://doi.org/10.22541/au.176312890.01167435/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.176312890.01167435/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a0065f4e9f144193',t:'MTc3OTU2MzU0Nw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();