oCELLoc: Predicts Suitable Cell Types in Spatial Transcriptomics and
scRNA-seq Data
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 
[aut, cre],
Vladyslav Honcharuk
[aut],
Alexis Vandenbon
[aut] |
| 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 |
Documentation:
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