Inference of heterogeneous effects in single-cell genetic perturbation screens

Inference of heterogeneous effects in single-cell genetic perturbation screens | 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 Article Inference of heterogeneous effects in single-cell genetic perturbation screens Lin Hou, Zichu Fu, Jin Gu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6623551/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Recent single-cell CRISPR screening experiments have combined the advances of genetic editing and single-cell technologies, leading to transcriptome-scale readouts of responses to perturbations at single-cell resolution. An outstanding question is how to efficiently identify heterogeneous effects of perturbations using these technologies. Here we present CausalPerturb, which leverages AI tools and causal analysis to dissect the heterogeneous landscape of perturbation effects. CausalPerturb disentangles transcriptome changes introduced by perturbations from those reflecting inherent cell-state variations. It provides nonparametric inferences of perturbation effects, enabling a range of downstream tasks including genetic interaction analysis, perturbation clustering and prioritization. We evaluated CausalPerturb through simulation studies and real datasets, and demonstrated its competence in characterizing latent confounding factors and discerning heterogeneous perturbation effects. The application of CausalPerturb unraveled novel genetic interactions between erythroid differentiation drivers. In particular, it pinpointed the role of the synergistic interaction between CBL and CNN1 in the S phase. Biological sciences/Genetics/Genetic interaction Biological sciences/Computational biology and bioinformatics/Computational models Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementalMaterialsv9.docx Inference of heterogeneous effects in single-cell genetic perturbation screens Cite Share Download PDF Status: Under Review 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. 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-6623551","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":459845799,"identity":"769160c2-720d-4863-a43c-2dfd06ae4801","order_by":0,"name":"Lin Hou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACAwYGxgMfGBh4wAgIGBuI0MJwcEYCqVoO8ySAmMRqMWfvMThs+6NOxpx/7TGJHww2shsOMD97gE+LZc8Zg8M5CYd5LGe8S5PsYUgz3nCAzdwAr8Nu5IC0HOAxuHHGTIKH4XDihgM8bBIEtVgk1IG1SP5h+E+kFoYEZh6D8z1m0jwMB4jQcuZYwcGetMNAW3iMrWUMko1nHmYzw6/lePPGBz9s6uwNzp8xvPmmwk6273jzM7xaEEAigQESTczEqQcC/gNEKx0Fo2AUjIIRBgCXSUrdvK0zRQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-4283-8501","institution":"Tsinghua University","correspondingAuthor":true,"prefix":"","firstName":"Lin","middleName":"","lastName":"Hou","suffix":""},{"id":459845800,"identity":"e4bf256c-69be-4693-879f-d3b53c75cd8f","order_by":1,"name":"Zichu Fu","email":"","orcid":"","institution":"Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Zichu","middleName":"","lastName":"Fu","suffix":""},{"id":459845801,"identity":"6800c890-13a0-453a-ad99-00d50aff296f","order_by":2,"name":"Jin Gu","email":"","orcid":"https://orcid.org/0000-0003-3968-8036","institution":"Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Jin","middleName":"","lastName":"Gu","suffix":""}],"badges":[],"createdAt":"2025-05-08 21:35:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6623551/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6623551/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83325347,"identity":"cb43a56a-dc36-4014-9934-1cf7756113f4","added_by":"auto","created_at":"2025-05-23 06:10:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":25040449,"visible":true,"origin":"","legend":"","description":"","filename":"causalperturbv9.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6623551/v1_covered_fb555c4a-3fb0-409f-b41f-a86bf4d6ce78.pdf"},{"id":83324950,"identity":"30c04247-ed5d-46bc-aaa5-9189d45dc1f8","added_by":"auto","created_at":"2025-05-23 06:02:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":26634990,"visible":true,"origin":"","legend":"Inference of heterogeneous effects in single-cell genetic perturbation screens","description":"","filename":"SupplementalMaterialsv9.docx","url":"https://assets-eu.researchsquare.com/files/rs-6623551/v1/8275548b0f45e792936576a1.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Inference of heterogeneous effects in single-cell genetic perturbation screens","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"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":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6623551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6623551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRecent single-cell CRISPR screening experiments have combined the advances of genetic editing and single-cell technologies, leading to transcriptome-scale readouts of responses to perturbations at single-cell resolution. 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