Package: topconfects 1.29.0

Paul Harrison

topconfects: Top Confident Effect Sizes

Rank results by confident effect sizes, while maintaining False Discovery Rate and False Coverage-statement Rate control. Topconfects is an alternative presentation of TREAT results with improved usability, eliminating p-values and instead providing confidence bounds. The main application is differential gene expression analysis, providing genes ranked in order of confident log2 fold change, but it can be applied to any collection of effect sizes with associated standard errors.

Authors:Paul Harrison [aut, cre]

topconfects_1.29.0.tar.gz
topconfects_1.29.0.zip(r-4.7)topconfects_1.29.0.zip(r-4.6)topconfects_1.29.0.zip(r-4.5)
topconfects_1.29.0.tgz(r-4.6-any)topconfects_1.29.0.tgz(r-4.5-any)
topconfects_1.29.0.tar.gz(r-4.7-any)topconfects_1.29.0.tar.gz(r-4.6-any)
topconfects_1.29.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
topconfects/json (API)

# Install 'topconfects' in R:
install.packages('topconfects', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pfh/topconfects/issues

On BioConductor:topconfects-1.29.0(bioc 3.24)topconfects-1.28.0(bioc 3.23)

geneexpressiondifferentialexpressiontranscriptomicsrnaseqmrnamicroarrayregressionmultiplecomparison

7.16 score 15 stars 2 packages 20 scripts 2 mentions 9 exports 18 dependencies

Last updated from:6e9f2dba59. Checks:1 WARNING, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING186
linux-devel-x86_64OK328
source / vignettesOK318
linux-release-x86_64OK285
macos-release-arm64OK151
macos-oldrel-arm64OK109
windows-develOK200
windows-releaseOK183
windows-oldrelOK191
wasm-releaseOK193

Exports:confects_plotconfects_plot_meconfects_plot_me2deseq2_confectsedger_confectslimma_confectsnest_confectsnormal_confectsrank_rank_plot

Dependencies:assertthatclicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Confident fold change
limma analysis | Standard limma analysis steps | Apply topconfects | Looking at the result | edgeR analysis | Standard edgeR analysis | DESeq2 analysis | Comparing results
Rendered fromfold_change.Rmdusingknitr::rmarkdown

Last update: 2024-12-09
Started: 2016-11-28

An overview of topconfects
If you want to find top confident differentially expressed genes | If you have a collection of effect sizes with standard errors | If you can calculate p-values for a collection of interval hypotheses | Visualizing results
Rendered froman_overview.Rmdusingknitr::rmarkdown

Last update: 2024-12-03
Started: 2019-09-20