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ASPEN is introduced as a statistical method that models allelic mean and variance using a sensitive mapping pipeline, a moderated beta-binomial framework, and adaptive shrinkage. It improves allelic imbalance detection by about 30% in both simulated and empirical datasets and quantifies changes in allelic variance. Applied to mouse brain organoids and T cells, ASPEN highlights incomplete Xinactivation, random monoallelic expression, and significant deviations in allelic variance.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/aspen-robust-detection-of-allelic-dynamics-in-single-cell-rna-seq/446964/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/aspen-robust-detection-of-allelic-dynamics-in-single-cell-rna-seq/446964.png","ImageObject",300,407,{"name":92,"@type":93},"Alexandar","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-02","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does ASPEN address in single-cell RNA-seq of F1 hybrids?","Question",{"text":112,"@type":113},"ASPEN addresses technical noise and sparsity in single-cell allelic measurements caused by low counts, which limits accurate inference of allelic expression.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does ASPEN estimate allelic expression and distinguish biological signal from noise?",{"text":117,"@type":113},"ASPEN models allelic mean and variance using a moderated beta-binomial model combined with adaptive shrinkage, along with a sensitive mapping pipeline to stabilize noisy allelic estimates.",{"name":119,"@type":110,"acceptedAnswer":120},"What biological findings result from applying ASPEN to mouse brain organoids and T cells?",{"text":121,"@type":113},"ASPEN identifies genes showing incomplete Xinactivation, random monoallelic expression, and significant deviations in allelic variance, including reduced variance in essential housekeeping genes and increased variance in neurodevelopmental and immune loci.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},446964,1790906515,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962090768658,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","OPEN ACCESS  \nCitation: Petrova V, Niu M, Vierbuchen TS, Wong ES (2025) ASPEN: Robust detection of allelic dynamics in single cell RNA-seq. PLoS Comput Biol 21(12): e1013837. [https://doi](https://doi). org/10.1371/journal.pcbi.1013837  \nEditor: Ilya Ioshikhes, . , CANADA  \nReceived: September 16, 2025  \nAccepted: December 13, 2025  \nPublished: December 19, 2025  \nCopyright: © 2025 Petrova et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData availability statement: ASPEN is  \navailable as an R package at [https://github](https://github). com/ewonglab/ASPEN The source code and data used to produce the results and analyses presented in this manuscript are available from Github repository: [https://github.com/](https://github.com/)[ ](https://github.com/)[ewonglab/ASPEN_manuscript](ewonglab/ASPEN_manuscript.)[.](ewonglab/ASPEN_manuscript.)  \n[Funding:](Funding: V.P. is)[ V.P. is](Funding: V.P. is) supported by an Australian Government Research Training Stipend  \nRESEARCH ARTICLE  \nASPEN: Robust detection of allelic dynamics in single cell RNA-seq  \nVeronika Petrova1,2, Muqing Niu1,2, Thomas S. Vierbuchen3,4, Emily S. Wong1,2*  \n1 Division of Molecular, Structural, and Computational Biology, Victor Chang Cardiac Research Institute, Darlinghurst, Australia, 2 School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia, 3 Developmental Biology Program, Sloan Kettering Institute for Cancer Research, New York, New York, United States of America, 4 Center for Stem Cell Biology, Sloan Kettering Institute for Cancer Research, New York, New York, United States of America  \n* [e.wong@victorchang.edu.au](e.wong@victorchang.edu.au)  \nAbstract  \nSingle-cell RNA-seq data from F1 hybrids provide a unique framework for dissecting complex regulatory mechanisms, but allelic measurements are limited by technical noise due to low counts. Here, we present ASPEN, a statistical method for modeling allelic mean and variance in single-cell transcriptomic data. ASPEN combines a sensitive mapping pipeline with a moderated beta-binomial model and adaptive shrinkage to distinguish allelic imbalance and changes to allelic variance in single cells. In both simulated and empirical datasets, ASPEN achieves a ~30% increase insensitivity over existing approaches for single-cell allelic imbalance detection. Applied to mouse brain organoids and T cells, ASPEN identifies genes with incomplete Xinactivation, random monoallelic expression, and significant deviations in allelic variance. These results reveal reduced variance in essential genes, consistent with tight regulatory control, and increased variance at neurodevelopmental and immune loci, indicative of regulatory flexibility.  \nAuthor summary  \nHybrid organisms inherit two distinct copies (alleles) of each gene, one from each parent. By measuring how much each allele is expressed in individual cells, we can detect regulatory differences that are invisible in bulk tissue samples. However, single-cell measurements are sparse, making it difficult to separate true biological signals from technical noise. We developed ASPEN, a statistical framework that stabilizes these noisy measurements to reliably estimate allelic expression. ASPEN improves the detection of allelic imbalance by up to 30% compared with existing methods and, uniquely, quantifies allelic variance, how much allele usage fluctuates across cells. Applying ASPEN to developing brain cells and immune cells, we discovered that essential “housekeeping”genes maintain remarkably stable allelic ratios, while genes involved in brain  \nPLOS Computational Biology | [https://doi.org/10.1371/journal.pcbi.1013837](https://doi.org/10.1371/journal.pcbi.1013837) December 19, 2025 1 / 26  \n[Scholarship. T.V. is](Scholarship. T.V. is) supp","cbCaim3lghGBfpfJ","https://ap.wps.com/l/cbCaim3lghGBfpfJ","pdf",2700688,26,"English","# Abstract\n# Author summary\n# Introduction","[{\"question\":\"What problem does ASPEN address in single-cell RNA-seq of F1 hybrids?\",\"answer\":\"ASPEN addresses technical noise and sparsity in single-cell allelic measurements caused by low counts, which limits accurate inference of allelic expression.\"},{\"question\":\"How does ASPEN estimate allelic expression and distinguish biological signal from noise?\",\"answer\":\"ASPEN models allelic mean and variance using a moderated beta-binomial model combined with adaptive shrinkage, along with a sensitive mapping pipeline to stabilize noisy allelic estimates.\"},{\"question\":\"What biological findings result from applying ASPEN to mouse brain organoids and T cells?\",\"answer\":\"ASPEN identifies genes showing incomplete Xinactivation, random monoallelic expression, and significant deviations in allelic variance, including reduced variance in essential housekeeping genes and increased variance in neurodevelopmental and immune loci.\"}]","ASPEN: Robust detection of allelic dynamics in single cell RNA-seq | PDF",1790717959,66]