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Adopts the general least squares-based data-driven normalization strategy developed by Heckmann et al. (2011) <doi:10.1186/1471-2105-12-250> to correct for technical variance in gene expression data generated via digital polymerase chain reaction (dPCR). Performs normalization of raw copy numbers and also calculates relative variability metrics that can be used to assess the impact of normalization on variance.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5) |
| Imports: | utils |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2026-04-16 |
| DOI: | 10.32614/CRAN.package.digiNORM (may not be active yet) |
| Author: | Grant C. O'Connell
|
| Maintainer: | Grant C. O'Connell <goconnell.phd at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | digiNORM citation info |
| CRAN checks: | digiNORM results |
| Reference manual: | digiNORM.html , digiNORM.pdf |
| Package source: | digiNORM_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 |
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