Package: divergence 1.29.0
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_1.29.0.tar.gz
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divergence_1.29.0.tgz(r-4.6-any)divergence_1.29.0.tgz(r-4.5-any)
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
divergence/json (API)
| # Install 'divergence' in R: |
| install.packages('divergence', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- 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-1.29.0(bioc 3.24)divergence-1.28.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:51938bf679. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 173 | ||
| linux-devel-x86_64 | NOTE | 271 | ||
| source / vignettes | OK | 231 | ||
| linux-release-x86_64 | NOTE | 299 | ||
| macos-release-arm64 | NOTE | 155 | ||
| macos-oldrel-arm64 | NOTE | 144 | ||
| windows-devel | NOTE | 204 | ||
| windows-release | NOTE | 213 | ||
| windows-oldrel | NOTE | 205 | ||
| wasm-release | OK | 107 |
Exports:computeChiSquaredTestcomputeMultivariateBinaryMatrixcomputeMultivariateDigitizationcomputeMultivariateSupportcomputeQuantileMatrixcomputeUnivariateDigitizationcomputeUnivariateSupportcomputeUnivariateTernaryMatrixfindMultivariateGammaWithSupportfindUnivariateGammaWithSupport
Dependencies:abindBiobaseBiocGenericsDelayedArraygenericsGenomicRangesIRangeslatticeMatrixMatrixGenericsmatrixStatsS4ArraysS4VectorsSeqinfoSparseArraySummarizedExperimentXVector
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 |