SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution

SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution

Abstract Background Understanding cellular heterogeneity within tissues hinges on knowledge of their spatial context. However, it is still challenging to accurately map cells to their spatial coordinates. Results We present SC2Spa, a deep learning-based approach that learns intricate spatial relatio...

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Main Authors: Linbu Liao, Esha Madan, António M. Palma, Hyobin Kim, Amit Kumar, Praveen Bhoopathi, Robert Winn, Jose Trevino, Paul Fisher, Cord Herbert Brakebusch, Gahyun Kim, Junil Kim, Rajan Gogna, Kyoung Jae Won
Format: Article
Language:English
Published: BMC 2025-06-01
Series:BMC Bioinformatics
Subjects:
Spatial transcriptomics
Spatial inference
Spatial mapping
Deep learning
Spatially variable genes
Online Access:https://doi.org/10.1186/s12859-025-06173-6
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https://doi.org/10.1186/s12859-025-06173-6

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