Package: divergence 1.23.0
Wikum Dinalankara
divergence: Divergence: Functionality for assessing omics data by divergence with respect to a baseline
This package provides functionality for performing divergence analysis as presented in Dinalankara et al, "Digitizing omics profiles by divergence from a baseline", PANS 2018. This allows the user to simplify high dimensional omics data into a binary or ternary format which encapsulates how the data is divergent from a specified baseline group with the same univariate or multivariate features.
Authors:
divergence_1.23.0.tar.gz
divergence_1.23.0.zip(r-4.5)divergence_1.23.0.zip(r-4.4)divergence_1.23.0.zip(r-4.3)
divergence_1.23.0.tgz(r-4.4-any)divergence_1.23.0.tgz(r-4.3-any)
divergence_1.23.0.tar.gz(r-4.5-noble)divergence_1.23.0.tar.gz(r-4.4-noble)
divergence_1.23.0.tgz(r-4.4-emscripten)divergence_1.23.0.tgz(r-4.3-emscripten)
divergence.pdf |divergence.html✨
divergence/json (API)
| # Install 'divergence' in R: |
| install.packages('divergence', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- breastTCGA_ER - ER positive or negative status of breast tumor samples
- breastTCGA_Group - Normal or Tumor status of breast samples
- breastTCGA_Mat - Gene expression for 260 genes in 887 breast samples
- msigdb_Hallmarks - Cancer Hallmark gene sets from the MSigDB collection
On BioConductor:divergence-1.23.0(bioc 3.21)divergence-1.22.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:ef1c130fc0. Checks:1 OK, 6 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Dec 29 2024 |
| R-4.5-win | NOTE | Dec 31 2024 |
| R-4.5-linux | NOTE | Dec 29 2024 |
| R-4.4-win | NOTE | Dec 31 2024 |
| R-4.4-mac | NOTE | Dec 29 2024 |
| R-4.3-win | NOTE | Dec 31 2024 |
| R-4.3-mac | NOTE | Dec 29 2024 |
Exports:computeChiSquaredTestcomputeMultivariateBinaryMatrixcomputeMultivariateDigitizationcomputeMultivariateSupportcomputeQuantileMatrixcomputeUnivariateDigitizationcomputeUnivariateSupportcomputeUnivariateTernaryMatrixfindMultivariateGammaWithSupportfindUnivariateGammaWithSupport
Dependencies:abindaskpassBiobaseBiocGenericscrayoncurlDelayedArraygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangeshttrIRangesjsonlitelatticeMatrixMatrixGenericsmatrixStatsmimeopensslR6S4ArraysS4VectorsSparseArraySummarizedExperimentsysUCSC.utilsXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ER positive or negative status of breast tumor samples | breastTCGA_ER |
| Normal or Tumor status of breast samples | breastTCGA_Group |
| Gene expression for 260 genes in 887 breast samples | breastTCGA_Mat |
| Compute chi-squared test | computeChiSquaredTest |
| Compute the binary matrix with digitized divergence coding | computeMultivariateBinaryMatrix |
| Perform binary digitization | computeMultivariateDigitization |
| Estimate the baseline support | computeMultivariateSupport |
| Compute quantile transformations | computeQuantileMatrix |
| Perform ternary digitization | computeUnivariateDigitization |
| Estimate the baseline support | computeUnivariateSupport |
| Compute the ternary matrix with digitized divergence coding | computeUnivariateTernaryMatrix |
| Find optimal gamma and corresponding support for list of feature sets | findMultivariateGammaWithSupport |
| Search for optimal gamma and associated support | findUnivariateGammaWithSupport |
| Cancer Hallmark gene sets from the MSigDB collection | msigdb_Hallmarks |