{"id":13093,"date":"2026-10-07T09:21:25","date_gmt":"2026-10-07T00:21:25","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&#038;p=13093"},"modified":"2026-10-07T09:21:25","modified_gmt":"2026-10-07T00:21:25","slug":"metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\/","title":{"rendered":"MetaQ: fast, scalable and accurate metacell inference via single-cell quantization &#8211; Fanpeng Song"},"content":{"rendered":"<p>In this talk, we discuss the paper &#8220;MetaQ: fast, scalable and accurate metacell inference via single-cell quantization&#8221; by Yunfan Li et al., <em>Nature Communications<\/em>, 2025.<\/p>\n<p>Abstract:<\/p>\n<section lang=\"en\" aria-labelledby=\"Abs1\" data-title=\"Abstract\">\n<div id=\"Abs1-section\" class=\"c-article-section\">\n<div id=\"Abs1-content\" class=\"c-article-section__content\">\n<p>To overcome the computational barriers of analyzing large-scale single-cell sequencing data, we introduce MetaQ, a metacell algorithm that scales to arbitrarily large datasets with linear runtime and constant memory usage. Inspired by cellular development, MetaQ conceptualizes each metacell as a collective ancestor of biologically similar cells. By quantizing cells into a discrete codebook, where each entry represents a metacell capable of reconstructing the original cells it quantizes, MetaQ identifies homogeneous cell subsets for efficient and accurate metacell inference. This approach reduces computational complexity from exponential to linear while maintaining or surpassing the performance of existing metacell algorithms. Extensive experiments demonstrate that MetaQ excels in downstream tasks such as cell type annotation, developmental trajectory inference, batch integration, and differential expression analysis. Thanks to its superior efficiency and effectiveness, MetaQ makes analyzing datasets with millions of cells practical, offering a powerful solution for single-cell studies in the era of high-throughput profiling.<\/p>\n<\/div>\n<\/div>\n<\/section>\n<div class=\"js-context-bar-sticky-point-mobile\" data-track-context=\"article body\"><\/div>\n<div data-test=\"article-recommendations\"><\/div>\n","protected":false},"excerpt":{"rendered":"<p>In this talk, we discuss the paper &#8220;MetaQ: fast, scalable and accurate metacell inference via single-cell quantization&#8221; by Yunfan Li et al., Nature Communications, 2025. Abstract: To overcome the computational &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;MetaQ: fast, scalable and accurate metacell inference via single-cell quantization &#8211; Fanpeng Song&#8221;<\/span><\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[219],"class_list":["post-13093","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-journal-club","cat_journal-club"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>MetaQ: fast, scalable and accurate metacell inference via single-cell quantization - Fanpeng Song - Biomedical Mathematics Group<\/title>\n<meta name=\"description\" content=\"In this talk, we discuss the paper &quot;MetaQ: fast, scalable and accurate metacell inference via single-cell quantization&quot; by Yunfan Li et al., Nature Communications, 2025.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MetaQ: fast, scalable and accurate metacell inference via single-cell quantization - Fanpeng Song - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\"In this talk, we discuss the paper &quot;MetaQ: fast, scalable and accurate metacell inference via single-cell quantization&quot; by Yunfan Li et al., Nature Communications, 2025.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ibs.re.kr\/bimag\/event\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\/\" \/>\n<meta property=\"og:site_name\" content=\"Biomedical Mathematics Group\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\\\/\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\\\/\",\"name\":\"MetaQ: fast, scalable and accurate metacell inference via single-cell quantization - Fanpeng Song - Biomedical Mathematics Group\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/#website\"},\"datePublished\":\"2026-10-07T00:21:25+00:00\",\"description\":\"In this talk, we discuss the paper \\\"MetaQ: fast, scalable and accurate metacell inference via single-cell quantization\\\" by Yunfan Li et al., Nature Communications, 2025.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\\\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/metaq-fast-scalable-and-accurate-metacell-inference-via-single-cell-quantization-fanpeng-song\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Events\",\"item\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/events\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"MetaQ: fast, scalable and accurate metacell inference via single-cell quantization &#8211; 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Fanpeng Song"}]},{"@type":"WebSite","@id":"https:\/\/www.ibs.re.kr\/bimag\/#website","url":"https:\/\/www.ibs.re.kr\/bimag\/","name":"Biomedical Mathematics Group","description":"\uae30\ucd08\uacfc\ud559\uc5f0\uad6c\uc6d0 \uc758\uc0dd\uba85\uc218\ud559\uadf8\ub8f9","publisher":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.ibs.re.kr\/bimag\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.ibs.re.kr\/bimag\/#organization","name":"IBS Biomedical Mathematics Group","url":"https:\/\/www.ibs.re.kr\/bimag\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.ibs.re.kr\/bimag\/#\/schema\/logo\/image\/","url":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2021\/02\/ibs-circle-1.png","contentUrl":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2021\/02\/ibs-circle-1.png","width":250,"height":250,"caption":"IBS Biomedical Mathematics Group"},"image":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#\/schema\/logo\/image\/"}}]}},"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false,"dimag-thumbnail":false,"twentyseventeen-featured-image":false,"twentyseventeen-thumbnail-avatar":false},"uagb_author_info":{"display_name":"Hyeong Jun Jang","author_link":"https:\/\/www.ibs.re.kr\/bimag\/author\/hyeong-jun-jang\/"},"uagb_comment_info":0,"uagb_excerpt":"In this talk, we discuss the paper &#8220;MetaQ: fast, scalable and accurate metacell inference via single-cell quantization&#8221; 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