A Probabilistic Approach to Visualize the Effect of Missing Data on PCA in Ancient Human Genomics

A Probabilistic Approach to Visualize the Effect of Missing Data on PCA in Ancient Human Genomics | 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 A Probabilistic Approach to Visualize the Effect of Missing Data on PCA in Ancient Human Genomics Susanne Zabel, Samira Breitling, Cosimo Posth, Kay Nieselt This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6105854/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 Principal Component Analysis (PCA) is widely used in population genetics to visualize genetic relationships. Methods like SmartPCA enable the projection of ancient samples despite missing genotype data due to degraded DNA, but do not quantify projection uncertainty, risking misinterpretation. We introduce TrustPCA, a probabilistic framework that models the impact of missing loci and provides uncertainty estimates for SmartPCA projections. Using simulations with high-coverage ancient human genomes, we show that TrustPCA accurately quantifies projection uncertainty. Applied to real ancient genomic data, our method improves the reliability of PCA interpretations. We provide TrustPCA as a user-friendly web tool for the research community. Ancient Genomics Missing Data Population Genetics Principal Component Analysis SmartPCA Uncertainty Full Text Additional Declarations No competing interests reported. Supplementary Files supplements.pdf Additionalfile1.xlsx Additionalfile2.txt Additionalfile3.xlsx Additionalfile4.csv 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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