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Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration

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Published in:PLoS Computational Biology
Format: Online Article RSS Article
Published: 2026
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container_title PLoS Computational Biology
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
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genre Journal Article
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institution FRELIP
journal_source_facet PLoS Computational Biology
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
Biology
Natural Sciences — Life Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Life Sciences
sub_discipline_facet Natural Sciences — Life Sciences
subject_display Biology
Natural Sciences — Life Sciences
Natural Sciences
Biology
Natural Sciences — Life Sciences
Natural Sciences
subject_facet Biology
Natural Sciences — Life Sciences
Natural Sciences
title Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
title_auth Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
title_full Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
title_fullStr Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
title_full_unstemmed Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
title_short Semi-parametric empirical bayes method for multiplet detection in snATAC-seq with probabilistic multi-omic integration
title_sort semi-parametric empirical bayes method for multiplet detection in snatac-seq with probabilistic multi-omic integration
topic Biology
Natural Sciences — Life Sciences
Natural Sciences
url https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013653