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digiNORM  

Data-Driven Digital PCR Normalization
View on CRAN: Click here


Download and install digiNORM package within the R console
Install from CRAN:
install.packages("digiNORM")

Install from Github:
library("remotes")
install_github("cran/digiNORM")

Install by package version:
library("remotes")
install_version("digiNORM", "0.1.0")



Attach the package and use:
library("digiNORM")
Maintained by
Grant C. O'Connell
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-16
Latest Update: 2026-04-16
Description:
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.
How to cite:
Grant C. O'Connell (2026). digiNORM: Data-Driven Digital PCR Normalization. R package version 0.1.0, https://cran.r-project.org/web/packages/digiNORM. Accessed 07 Jun. 2026.
Previous versions and publish date:
No previous versions
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View digiNORM citation profile
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Complete documentation for digiNORM
Functions, R codes and Examples using the digiNORM R package
Full digiNORM package functions and examples
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