SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution
SC2Spa is a robust and accurate approach to provide single cells with their spatial location and identify spatially meaningful genes.
Authors
- Rajan Gogna (ORCID: https://orcid.org/0000-0001-7304-7692)
- Praveen Bhoopathi (ORCID: https://orcid.org/0000-0003-1379-4199)
- Robert A. Winn (ORCID: https://orcid.org/0000-0001-5948-9291)
- Junil Kim (ORCID: https://orcid.org/0000-0002-1202-1808)
- Paul B. Fisher
- Esha Madan (ORCID: https://orcid.org/0000-0002-4941-0612)
- Cord Brakebusch (ORCID: https://orcid.org/0000-0002-9342-1634)
- Jose Trevino (ORCID: https://orcid.org/0009-0002-2007-5897)
- Kyoung‐Jae Won (ORCID: https://orcid.org/0000-0002-2924-9630)
- Linbu Liao (ORCID: https://orcid.org/0000-0002-6103-0700)
- Antonio Palma (ORCID: https://orcid.org/0000-0001-5229-4985)
- Hyobin Kim (ORCID: https://orcid.org/0000-0002-4856-7415)
- Amit Kumar (ORCID: https://orcid.org/0000-0002-3079-2067)
- Gahyun Kim (ORCID: https://orcid.org/0000-0002-8454-2821)
Institutions
- University of Copenhagen (DK)
- Soongsil University (KR)
- University of Lisbon (PT)
- Virginia Commonwealth University (US)
- Universidade Politécnica de Lisboa (PT)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1186/s12859-025-06173-6
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Cedars-Sinai Medical Center
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea