SurvSPro: Survival Prediction with Spatially Adjusted Protein Summaries

A survival prediction framework using spatially adjusted protein summaries from spatial proteomics data, including imaging mass cytometry data. Cell-level protein intensities are modeled with spatial spline regression to estimate spatially adjusted mean expression and residual variance. Methodological details are described in Ahn et al. (2026) <doi:10.64898/2026.06.08.730964>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: dplyr, mgcv, survival, sp
Suggests: testthat (≥ 3.0.0)
Published: 2026-06-19
DOI: 10.32614/CRAN.package.SurvSPro (may not be active yet)
Author: Seungjun Ahn ORCID iD [cre, aut], Eun Jeong Oh ORCID iD [aut], Diddier Prada [ctb], Ali Shojaie [ctb]
Maintainer: Seungjun Ahn <seungjun.ahn at mountsinai.org>
License: GPL-3
NeedsCompilation: no
CRAN checks: SurvSPro results

Documentation:

Reference manual: SurvSPro.html , SurvSPro.pdf

Downloads:

Package source: SurvSPro_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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