Introduction | Installation | Quick start | Quantifying batch effects using HVP | Class: SummarizedExperiment / SingleCellExperiment | Class: Seurat | Testing the statistical significance of batch effects | Simulating microarray gene expression data | HVP: Theory | Batch effects | Hierarchical variance partitioning | Session info | References
Package: HVP 1.3.0
Wei Xin Chan
HVP: Hierarchical Variance Partitioning
HVP is a quantitative batch effect metric that estimates the proportion of variance associated with batch effects in a data set.
Authors:
HVP_1.3.0.tar.gz
HVP_1.3.0.zip(r-4.7)HVP_1.3.0.zip(r-4.6)HVP_1.3.0.zip(r-4.5)
HVP_1.3.0.tgz(r-4.6-any)HVP_1.3.0.tgz(r-4.5-any)
HVP_1.3.0.tar.gz(r-4.7-any)HVP_1.3.0.tar.gz(r-4.6-any)
HVP_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
HVP/json (API)
| # Install 'HVP' in R: |
| install.packages('HVP', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:HVP-1.3.0(bioc 3.24)HVP-1.2.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
singlecelltranscriptomicsgeneexpressionbatcheffect
Last updated from:fc5632ed7e. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 200 | ||
| linux-devel-x86_64 | NOTE | 245 | ||
| source / vignettes | OK | 300 | ||
| linux-release-x86_64 | NOTE | 279 | ||
| macos-release-arm64 | NOTE | 117 | ||
| macos-oldrel-arm64 | NOTE | 149 | ||
| windows-devel | NOTE | 148 | ||
| windows-release | NOTE | 135 | ||
| windows-oldrel | NOTE | 129 | ||
| wasm-release | OK | 174 |
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Hierarchical variance partitioning (HVP) | HVP HVP,data.frame-method HVP,Matrix-method HVP,matrix-method HVP,Seurat-method HVP,SummarizedExperiment-method |
| HVP results class | hvp-class |
| Plot results of permutation test | plot,hvp,missing-method |
| Sigmoid function | sigmoid |
| Simulate log-transformed microarray gene expression data | simulateMicroarray |
| Splits subsettable objects according to their columns | splitCols |
