Cell Layers: uncovering clustering structure in unsupervised single-cell transcriptomic analysis
Cell Layers: uncovering clustering structure in unsupervised single-cell transcriptomic analysis
About this item
Full title
Author / Creator
Publisher
England: Oxford University Press
Journal title
Language
English
Formats
Publication information
Publisher
England: Oxford University Press
Subjects
More information
Scope and Contents
Contents
Abstract
Motivation
Unsupervised clustering of single-cell transcriptomics is a powerful method for identifying cell populations. Static visualization techniques for single-cell clustering only display results for a single resolution parameter. Analysts will often evaluate more than one resolution parameter but then only report one.
Results
We developed Cell Layers, an interactive Sankey tool for the quantitative investigation of gene expression, co-expression, biological processes and cluster integrity across clustering resolutions. Cell Layers enhances the interpretability of single-cell clustering by linking molecular data and cluster evaluation metrics, providing novel insight into cell populations.
Availability and implementation
https://github.com/apblair/CellLayers....
Alternative Titles
Full title
Cell Layers: uncovering clustering structure in unsupervised single-cell transcriptomic analysis
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9362878
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9362878
Other Identifiers
ISSN
2635-0041
E-ISSN
2635-0041
DOI
10.1093/bioadv/vbac051
