Article

spaTransfer: transfer learning for single-cell and spatial transcriptomics data using non-negative matrix factorization

2025-12-16

Abstract excerpt

Recent advances in spatially-resolved transcriptomics have enabled profiling of gene expression in a spatial context, which has led to the generation of large-scale single-cell and spatial atlases with computationally-derived cell type or spatial domain labels. An increasingly important task with these data has become the transfer of cell type or spatial domain annotations from a given reference (or source) atlas...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 83cc5c7d-c285-5c83-97fb-5bdb3ee91955
DOI: 10.64898/2025.12.12.694021

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

spaTransfer: transfer learning for single-cell and spatial transcriptomics data using non-negative matrix factorizationDOI 10.64898/2025.12.12.694021Read

Towards Cross-Sample Alignment for Multi-Modal Representation Learning in Spatial TranscriptomicsSemantic proximity Read

SpatialMap: A Scalable Deep Learning Method for Cell Typing in Subcellular Spatial TranscriptomicsSemantic proximity Read

spOT-NMF: Optimal Transport-Based Matrix Factorization for Accurate Deconvolution of Spatial TranscriptomicsSemantic proximity Read

Exploit Spatially Resolved Transcriptomic Data to Infer Cellular Features from Pathology Imaging DataSemantic proximity Read

Query to reference single-cell integration with transfer learningSemantic proximity Read

STEM: A Method for Mapping Single-cell and Spatial Transcriptomics Data with Transfer LearningSemantic proximity Read

Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomicsSemantic proximity Read

Flexible Analysis of Spatial Transcriptomics Data (FAST): A Deconvolution ApproachSemantic proximity Read

Multi-Modal Foundation Model with Whole-Slide Attention Enables Transferrable Digital Pathology at Single-Cell ResolutionSemantic proximity Read

JADE: Joint Alignment and Deep Embedding for Multi-Slice Spatial TranscriptomicsSemantic proximity Read

Spatial Transcriptomics Expression Prediction from Histopathology Based on Cross-Modal Mask Reconstruction and Contrastive LearningSemantic proximity Read

SNMF: Ultrafast, Spatially-Aware Deconvolution for Spatial TranscriptomicsSemantic proximity Read