Package: digiNORM 0.1.0
Grant C. OConnell
digiNORM: Data-Driven Digital PCR Normalization
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.
Authors:
digiNORM_0.1.0.tar.gz
digiNORM_0.1.0.tar.gz(r-4.7-any)digiNORM_0.1.0.tar.gz(r-4.6-any)
digiNORM_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
digiNORM/json (API)
| # Install 'digiNORM' in R: |
| install.packages('digiNORM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- multi_cond_data - Example dataset from a multi-condition dPCR experiment.
- single_cond_data - Example dataset from a single condition dPCR experiment.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:1a6e3ef34d. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 120 | ||
| source / vignettes | OK | 142 | ||
| linux-release-x86_64 | OK | 106 | ||
| wasm-release | OK | 87 |
Exports:correction_factorsdigi_normnormalization_weightsrelative_variability
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Data-Driven Digital PCR Normalization | digiNORM-package |
| Retrieve correction factors from digiNORM output | correction_factors |
| Normalize copy numbers using digiNORM | digi_norm |
| Example dataset from a multi-condition dPCR experiment. | multi_cond_data |
| Retrieve target weights from digiNORM output | normalization_weights |
| Retrieve relative variability metrics from digiNORM output | relative_variability |
| Example dataset from a single condition dPCR experiment. | single_cond_data |
| Summarize digiNORM normalization | summary.digi_norm |