Supervised dimensionality reduction for exploration of single-cell data by Hybrid Subset Selection -...
Supervised dimensionality reduction for exploration of single-cell data by Hybrid Subset Selection - Linear Discriminant Analysis
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Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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Language
English
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Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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Contents
Single-cell technologies generate large, high-dimensional datasets encompassing a diversity of omics. Dimensionality reduction enables visualization of data by representing cells in two-dimensional plots that capture the structure and heterogeneity of the original dataset. Visualizations contribute to human understanding of data and are useful for...
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Full title
Supervised dimensionality reduction for exploration of single-cell data by Hybrid Subset Selection - Linear Discriminant Analysis
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TN_cdi_proquest_journals_2617115959
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2617115959
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E-ISSN
2692-8205
DOI
10.1101/2022.01.06.475279
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https://www.proquest.com/docview/2617115959?pq-origsite=primo&accountid=13902
