CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis
Here, we present a novel model, named CosGeneGate, to select marker genes for more effective marker selections. CosGeneGate is inspired by combining the advantages of selecting marker genes based on both cell-type classification accuracy and marker gene specific expression patterns. We demonstrate the better performance of the marker genes selected by CosGeneGate for various downstream analyses than the existing methods with both public datasets and newly sequenced datasets. The non-redundant marker genes identified by CosGeneGate for major cell types and tissues in human can be found at the website as follows: https://github.com/VivLon/CosGeneGate/blob/main/marker gene list.xlsx.
Authors
- Tianyu Liu (ORCID: https://orcid.org/0000-0002-9412-6573)
- Le Zhang (ORCID: https://orcid.org/0000-0002-4860-831X)
- Stephen M. Strittmatter (ORCID: https://orcid.org/0000-0001-8188-3092)
- Chuan He (ORCID: https://orcid.org/0000-0002-9983-7526)
- Wenxin Long
- Hongyu Zhao (ORCID: https://orcid.org/0009-0004-0091-8281)
- Yuge Wang (ORCID: https://orcid.org/0000-0003-3005-6163)
- Zhiyuan Cao
Institutions
- Pennsylvania State University (US)
- Yale University (US)
Publication Details
- Journal
- Briefings in Bioinformatics
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1093/bib/bbae626
- Citations
- 2
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- National Institutes of Health