Leveraging gene correlations in single cell transcriptomic data
New insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene-gene correlations.
Authors
- Arthur D. Lander (ORCID: https://orcid.org/0000-0002-4380-5525)
- Emmanuel Dollinger (ORCID: https://orcid.org/0000-0002-2562-7980)
- Kai Silkwood
- Joshua Gervin
- Qing Nie (ORCID: https://orcid.org/0000-0002-8804-3368)
- Scott X. Atwood (ORCID: https://orcid.org/0000-0001-7407-9792)
Institutions
- University of California, Irvine (US)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1186/s12859-024-05926-z
- Citations
- 7
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 1.64
Funders
- National Science Foundation
- National Institutes of Health