CRAmed: A conditional randomization test for high-dimentional mediation analysis in sparse microbiome data

CRAmed: A conditional randomization test for high-dimentional mediation analysis in sparse microbiome data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article CRAmed: A conditional randomization test for high-dimentional mediation analysis in sparse microbiome data Tiantian Liu, Xiangnan Xu, Tao Wang, Peirong Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4516321/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Numerous microbiome studies have revealed significant associations between the microbiome and human health and disease. These findings have motivated researchers to explore the causal role of microbiome in human complex traits and diseases. However, the complexities of microbiome data pose challenges for statistical analysis and interpretation of causal effects. Results: We introduced a novel statistical framework, CRAmed, for inferring the mediating role of the microbiome between treatment and outcome. CRAmed improved the interpretability of the mediation analysis by decomposing the natural indirect effect into two parts, corresponding to the presence-absence and abundance of a microbe, respectively. Comprehensive simulations demonstrated the superior performance of CRAmed in recall, precision, and F1 score, with a notable level of robustness, compared to existing mediation analysis methods. Furthermore, two real data applications illustrated the effectiveness and inter pretability of CRAmed. Conclusion: Our research revealed that CRAmed holds promise for uncovering the mediating role of the microbiome and understanding of the factors influencing host health. casual mediation analysis conditional randomization test high dimensionality zero-inflated negative binomial microbiome data Full Text Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4516321","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":312564817,"identity":"5119cc53-95ee-4e51-ad05-e4c43a8d1342","order_by":0,"name":"Tiantian Liu","email":"","orcid":"","institution":"China Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Tiantian","middleName":"","lastName":"Liu","suffix":""},{"id":312564819,"identity":"8aa60be5-4105-4e51-bf44-0e6eda006d1c","order_by":1,"name":"Xiangnan Xu","email":"","orcid":"","institution":"Humboldt-Universität zu Berlin","correspondingAuthor":false,"prefix":"","firstName":"Xiangnan","middleName":"","lastName":"Xu","suffix":""},{"id":312564825,"identity":"7c024695-c0b3-4dda-8bae-bd7e02799b69","order_by":2,"name":"Tao Wang","email":"","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Wang","suffix":""},{"id":312564827,"identity":"287a71f2-929c-479b-8b6d-db4557ca1c4e","order_by":3,"name":"Peirong Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYLCCDwxsYFqCaB2MMxjYJEjTwswDVU2cFnPpM2bSNn/46gwOMB+8zcNgl0dQi2VfWpp0bhubhMEBtmRrHobkYoJaDM4wH5PObQBp4TGT5mE4kNhAWAtjm7TFH5AW/m/EagHawsAGtoWNOC2WPWzJlr1tbJIzD7MZW84xSCasxZyHx/DGjz/H+PmONz+88abCjgiHQahjwNhB4hKjpYYIpaNgFIyCUTBiAQAnazEthMXnEAAAAABJRU5ErkJggg==","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":true,"prefix":"","firstName":"Peirong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-06-02 08:46:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4516321/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4516321/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58549327,"identity":"42039731-4c07-454e-a938-0875aa21bffa","added_by":"auto","created_at":"2024-06-18 06:29:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1670349,"visible":true,"origin":"","legend":"","description":"","filename":"CRAmedmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4516321/v1_covered_533c1bbc-e74a-466b-ae4c-ed570779efc9.pdf"},{"id":58383344,"identity":"63764a9c-ce31-446c-996b-16d644204c3b","added_by":"auto","created_at":"2024-06-14 18:12:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1673429,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4516321/v1/7aef9fe1bc4b0e926b3f64e0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CRAmed: A conditional randomization test for high-dimentional mediation analysis in sparse microbiome data","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":" casual mediation analysis, conditional randomization test, high dimensionality, zero-inflated negative binomial, microbiome data","lastPublishedDoi":"10.21203/rs.3.rs-4516321/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4516321/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Numerous microbiome studies have revealed significant associations between the microbiome and human health and disease. 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