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Provides unified workflows for quality control, normalization, and visualization of proteomic and metabolomic data. The package simplifies preprocessing through automated imputation, scaling, and principal component analysis (PCA)-based exploratory analysis, enabling researchers to prepare omics datasets efficiently for downstream statistical and machine learning analyses.
| Version: | 0.1.1 |
| Imports: | ggplot2, stats, utils |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-11-11 |
| DOI: | 10.32614/CRAN.package.OmicsPrepR |
| Author: | Isaac Osei [aut, cre], Dennis Opoku Boadu [aut], Chettupally Anil Carie [aut] |
| Maintainer: | Isaac Osei <ikemillar65 at gmail.com> |
| BugReports: | https://github.com/ikemillar/OmicsPrepR/issues |
| License: | GPL-3 |
| URL: | https://github.com/ikemillar/OmicsPrepR |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | OmicsPrepR results |
| Reference manual: | OmicsPrepR.html , OmicsPrepR.pdf |
| Package source: | OmicsPrepR_0.1.1.tar.gz |
| Windows binaries: | r-devel: OmicsPrepR_0.1.1.zip, r-release: OmicsPrepR_0.1.1.zip, r-oldrel: OmicsPrepR_0.1.1.zip |
| macOS binaries: | r-release (arm64): OmicsPrepR_0.1.1.tgz, r-oldrel (arm64): OmicsPrepR_0.1.1.tgz, r-release (x86_64): OmicsPrepR_0.1.1.tgz, r-oldrel (x86_64): OmicsPrepR_0.1.1.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.
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