SPACO: Spatial Component Analysis for Spatial Sequencing Data
Spatial components offer tools for dimension reduction and
spatially variable gene detection for high dimensional spatial transcriptomics
data. Construction of a projection onto low-dimensional feature space of
spatially dependent metagenes offers pre-processing to clustering, testing for
spatial variability and denoising of spatial expression patterns. For more
details, see Koehler et al. (2026) <doi:10.1093/bioinformatics/btag052>.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.2.3) |
| Imports: |
ggplot2, Seurat (≥ 5.3.0), tibble, ggforce, methods, rARPACK, tidyr, mgcv, scales, Matrix (≥ 1.5) |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2026-03-31 |
| DOI: |
10.32614/CRAN.package.SPACO (may not be active yet) |
| Author: |
David Köhler 
[aut, cre] |
| Maintainer: |
David Köhler <koehler at imbie.uni-bonn.de> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
yes |
| CRAN checks: |
SPACO results [issues need fixing before 2026-04-14] |
Documentation:
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