Overview | Installation | Data normalization; computing and plotting feature dominance | Normalization functions (e.g. quantile normalization) | Example 1: SummarizedExperiment object | Example 2: dataframe object | Calculation functions (e.g. entropy) | Visualization functions (2-, 3-, and N-dimensions) | Example 1: Two Dimensions with plot_rope() | Example 2: Three Dimensions with plot_triangle() | Example 3: N-Dimensions with plot_circle() | Session Info
Package: dominatR 1.1.0
Simon Lizarazo
dominatR: Feature Dominance-based R Package for Genomic Data
dominatR is an R package for quantifying and visualizing feature dominance in datasets. dominatR applies concepts drawn from physics such as center of mass and shannon's entropy to effectively visualize features (e.g. genes) that are present within a specific context or condition. The package integrates, dataframes, matrices and SummerizedExperiment objects and is able to perform common genomic normalization methods. The key aspect is the generation of plots that serve to highlight context-relevant feature dominance.
Authors:
dominatR_1.1.0.tar.gz
dominatR_1.1.0.zip(r-4.7)dominatR_1.1.0.zip(r-4.6)dominatR_1.1.0.zip(r-4.5)
dominatR_1.1.0.tgz(r-4.6-any)dominatR_1.1.0.tgz(r-4.5-any)
dominatR_1.1.0.tar.gz(r-4.7-any)dominatR_1.1.0.tar.gz(r-4.6-any)
dominatR_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dominatR/json (API)
| # Install 'dominatR' in R: |
| install.packages('dominatR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/vanbortlelab/dominatr/issues
Pkgdown/docs site:https://vanbortlelab.github.io
On BioConductor:dominatR-1.1.0(bioc 3.24)dominatR-1.0.0(bioc 3.23)
visualizationnormalizationclassificationgeneexpression
Last updated from:f53dfa0bad. Checks:1 NOTE, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 199 | ||
| linux-devel-x86_64 | OK | 377 | ||
| source / vignettes | OK | 306 | ||
| linux-release-x86_64 | OK | 376 | ||
| macos-release-arm64 | OK | 211 | ||
| macos-oldrel-arm64 | OK | 273 | ||
| windows-devel | OK | 213 | ||
| windows-release | OK | 283 | ||
| windows-oldrel | OK | 324 | ||
| wasm-release | OK | 158 |
Exports:centmasscpm_normalizationentropyminmax_normalizationplot_circleplot_circle_frequencyplot_ropeplot_triangleQentropyquantile_normalizationrpkm_normalizationtpm_normalization
Dependencies:abindbase64encBiobaseBiocGenericsclicpp11DelayedArraydplyrfarvergenericsGenomicRangesgeomtextpathggforceggnewscaleggplot2gluegtableIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatspillarpkgconfigpolyclipR6RColorBrewerrlangS4ArraysS4VectorsS7scalesSeqinfoSparseArraystringiSummarizedExperimentsystemfontstextshapingtibbletidyselecttweenrutf8vctrsviridisLitewithrXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute the "center of mass" for rows of a data frame or SummarizedExperiment | centmass |
| Counts Per Million normalization | cpm_normalization |
| Compute Shannon Entropy on row-normalized data | entropy |
| Min-Max Normalization | minmax_normalization |
| Circular Dominance Plot (More than 3 variables) | plot_circle |
| Dominance–Entropy Frequency Plot | plot_circle_frequency |
| Rope (binary) dominance plot | plot_rope |
| Triangle (ternary) dominance plot | plot_triangle |
| Compute Q-Entropy using existing row-normalized data + Entropy | Qentropy |
| Quantile Normalization | quantile_normalization |
| RPKM Normalization | rpkm_normalization |
| TPM Normalization | tpm_normalization |