Spatially aware dimension reduction for spatial transcriptomics
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Abstract
Spatial transcriptomics are a collection of genomic technologies that have enabled transcriptomic profiling on tissues with spatial localization information. Analyzing spatial transcriptomic data is computationally challenging, as the data collected from various spatial transcriptomic technologies are often noisy and display substantial spatial correlation across tissue locations. Here, we develop a spatially-aware dimension reduction method, SpatialPCA, that can extract a low dimensional representation of the spatial transcriptomics data with biological signal and preserved spatial correlation structure, thus unlocking many existing computational tools previously developed in single-cell RNAseq studies for…
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251
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2Topics & keywords
Topics
Keywords
- Transcriptome
- Spatial analysis
- Inference
- Computer science
- Computational biology
- Biology
- Artificial intelligence
- Genetics
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