Introduction | An example: RNA-Seq differential expression | FDR control | Diagnostic plots | Estimated weights | Decision boundary | Raw versus adjusted p-values | FWER control with IHW | Other data types, and how to choose the covariate | Criteria for choosing a covariate | Examples | Why are the different covariate criteria necessary? | Diagnostic plots for the covariate | Scatter plots | Stratified p-value histograms | Further reading about appropriate covariates | Advanced usage: Working with incomplete p-value lists | References
Package: IHW 1.41.0
Nikos Ignatiadis
IHW: Independent Hypothesis Weighting
Independent hypothesis weighting (IHW) is a multiple testing procedure that increases power compared to the method of Benjamini and Hochberg by assigning data-driven weights to each hypothesis. The input to IHW is a two-column table of p-values and covariates. The covariate can be any continuous-valued or categorical variable that is thought to be informative on the statistical properties of each hypothesis test, while it is independent of the p-value under the null hypothesis.
Authors:
IHW_1.41.0.tar.gz
IHW_1.41.0.zip(r-4.7)IHW_1.41.0.zip(r-4.6)IHW_1.41.0.zip(r-4.5)
IHW_1.41.0.tgz(r-4.6-any)IHW_1.41.0.tgz(r-4.5-any)
IHW_1.41.0.tar.gz(r-4.7-any)IHW_1.41.0.tar.gz(r-4.6-any)
IHW_1.41.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
IHW/json (API)
| # Install 'IHW' in R: |
| install.packages('IHW', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:IHW-1.41.0(bioc 3.24)IHW-1.40.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologymultiplecomparisonrnaseq
Last updated from:ea4f335e68. Checks:1 WARNING, 4 NOTE, 2 OK, 3 ERROR. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 185 | ||
| linux-devel-x86_64 | NOTE | 227 | ||
| source / vignettes | OK | 300 | ||
| linux-release-x86_64 | NOTE | 221 | ||
| macos-release-arm64 | NOTE | 92 | ||
| macos-oldrel-arm64 | NOTE | 128 | ||
| windows-devel | ERROR | 158 | ||
| windows-release | ERROR | 311 | ||
| windows-oldrel | ERROR | 312 | ||
| wasm-release | OK | 197 |
Exports:adj_pvaluesalphaas.data.framecovariate_typecovariatesget_bh_thresholdgroups_by_filtergroups_factorihwm_groupsnbinsnfoldsnrowplotpvaluesregularization_termrejected_hypothesesrejectionsshowthresholdsweighted_pvaluesweights
Dependencies:BiocGenericsfdrtoolgenericslpsymphonyslam
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Data-driven threshold of Benjamini Hochberg Procedure | get_bh_threshold |
| Stratify hypotheses based on increasing value of the covariate | groups_by_filter |
| ihw: Main function for Independent Hypothesis Weighting | ihw ihw.default ihw.formula |
| ihw.DESeqResults: IHW method dispatching on DESeqResults objects | ihw.DESeqResults |
| An S4 class to represent the ihw output. | adj_pvalues adj_pvalues,ihwResult-method alpha alpha,ihwResult-method as.data.frame,ihwResult-method as.data.frame_ihwResult covariates covariates,ihwResult-method covariate_type covariate_type,ihwResult-method groups_factor groups_factor,ihwResult-method ihwResult ihwResult-class m_groups m_groups,ihwResult-method nbins nbins,ihwResult-method nfolds nfolds,ihwResult-method nrow,ihwResult-method pvalues pvalues,ihwResult-method regularization_term regularization_term,ihwResult-method rejected_hypotheses rejected_hypotheses,ihwResult-method rejections rejections,ihwResult-method show,ihwResult-method thresholds thresholds,ihwResult-method weighted_pvalues weighted_pvalues,ihwResult-method weights,ihwResult-method |
| Plot functions for IHW | plot,ihwResult-method |
