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Picks the suitable cell types in spatial and scRNA-seq data using shrinkage methods. The package includes curated reference gene expression profiles for human and mouse cell types, facilitating immediate application to common spatial transcriptomics or scRNA datasets. Additionally, users can input custom reference data to support tissue- or experiment-specific analyses.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | glmnet, utils, stats, ggplot2, rlang, reshape2 |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2025-12-22 |
| DOI: | 10.32614/CRAN.package.oCELLoc |
| Author: | Afeefa Zainab |
| Maintainer: | Afeefa Zainab <afeeffazainab at gmail.com> |
| License: | MIT + file LICENSE |
| URL: | https://doi.org/10.64898/2025.12.11.693812 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | oCELLoc results |
| Reference manual: | oCELLoc.html , oCELLoc.pdf |
| Package source: | oCELLoc_1.0.0.tar.gz |
| Windows binaries: | r-devel: oCELLoc_1.0.0.zip, r-release: oCELLoc_1.0.0.zip, r-oldrel: oCELLoc_1.0.0.zip |
| macOS binaries: | r-release (arm64): oCELLoc_1.0.0.tgz, r-oldrel (arm64): oCELLoc_1.0.0.tgz, r-release (x86_64): oCELLoc_1.0.0.tgz, r-oldrel (x86_64): oCELLoc_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.