A highly scalable approach to topic modelling in single-cell data by approximate pseudobulk projecti...
A highly scalable approach to topic modelling in single-cell data by approximate pseudobulk projection
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Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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Language
English
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Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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Contents
Probabilistic topic modelling has become essential in many types of single-cell data analysis. Based on probabilistic topic assignments in each cell, we identify the latent representation of cellular states, and topic-specific gene frequency vectors provide interpretable bases to be compared with known cell-type-specific marker genes. However, fitt...
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Full title
A highly scalable approach to topic modelling in single-cell data by approximate pseudobulk projection
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TN_cdi_proquest_journals_2931022068
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2931022068
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E-ISSN
2692-8205
DOI
10.1101/2024.02.21.581497
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https://www.proquest.com/docview/2931022068?pq-origsite=primo&accountid=13902
