Adding highly variable genes to spatially variable genes can improve cell type clustering performance in spatial transcriptomics data
All data and code used in this evaluation study can be found in the following link: https://github.com/lanagarmire/ST_benchmark.
Authors
- Lana X. Garmire
- Jian Kang (ORCID: https://orcid.org/0000-0002-5643-2668)
- Qianhui Huang (ORCID: https://orcid.org/0000-0002-3292-7519)
- Stefan Stanojevic (ORCID: https://orcid.org/0009-0007-6076-3586)
- Yijun Li (ORCID: https://orcid.org/0000-0003-0513-9565)
- Bing He (ORCID: https://orcid.org/0000-0003-1719-9290)
- Zheng Jing (ORCID: https://orcid.org/0000-0003-0111-5056)
Institutions
- University of Michigan (US)
Publication Details
- Journal
- Bioinformatics Advances
- Published
- 2025-11-20
- DOI
- https://doi.org/10.1093/bioadv/vbaf285
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of General Medical Sciences
- National Institute of Child Health and Human Development
- U.S. National Library of Medicine
- Eunice Kennedy Shriver National Institute of Child Health and Human Development