nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes
Abstract Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, a scalable approach to identify spatially variable genes based on nearest-neighbor Gaussian proces...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-07-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-39748-z |