Package: preprocessCore 1.75.1

Ben Bolstad

preprocessCore: A collection of pre-processing functions

A library of core preprocessing routines.

Authors:Ben Bolstad <[email protected]>

preprocessCore_1.75.1.tar.gz
preprocessCore_1.75.1.zip(r-4.7-x86_64)preprocessCore_1.75.1.zip(r-4.7-arm64)preprocessCore_1.75.1.zip(r-4.6-x86_64)preprocessCore_1.75.1.zip(r-4.6-arm64)preprocessCore_1.75.1.zip(r-4.5-x86_64)
preprocessCore_1.75.1.tgz(r-4.6-x86_64)preprocessCore_1.75.1.tgz(r-4.6-arm64)preprocessCore_1.75.1.tgz(r-4.5-x86_64)preprocessCore_1.75.1.tgz(r-4.5-arm64)
preprocessCore_1.75.1.tar.gz(r-4.7-arm64)preprocessCore_1.75.1.tar.gz(r-4.7-x86_64)preprocessCore_1.75.1.tar.gz(r-4.6-arm64)preprocessCore_1.75.1.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
preprocessCore/json (API)

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

Bug tracker:https://github.com/bmbolstad/preprocesscore/issues

Uses libs:
  • openblas– Optimized BLAS

On BioConductor:preprocessCore-1.75.1(bioc 3.24)preprocessCore-1.74.0(bioc 3.23)

infrastructureopenblas

12.42 score 19 stars 225 packages 2.1k scripts 30k downloads 146 mentions 39 exports 0 dependencies

Last updated from:5f4522fcbc. Checks:1 ERROR, 8 WARNING, 6 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR147
linux-devel-arm64WARNING107
linux-devel-x86_64WARNING220
source / vignettesOK198
linux-release-arm64WARNING151
linux-release-x86_64WARNING297
macos-release-arm64WARNING104
macos-release-x86_64WARNING219
macos-oldrel-arm64WARNING90
macos-oldrel-x86_64WARNING148
windows-devel-arm64OK206
windows-devel-x86_64OK121
windows-release-arm64OK199
windows-release-x86_64OK80
windows-oldrel-x86_64OK72
wasm-releaseFAIL107

Exports:colSummarizeAvgcolSummarizeAvgLogcolSummarizeBiweightcolSummarizeBiweightLogcolSummarizeLogAvgcolSummarizeLogMediancolSummarizeMediancolSummarizeMedianLogcolSummarizeMedianpolishcolSummarizeMedianpolishLogconvert.group.labelsnormalize.quantilesnormalize.quantiles.determine.targetnormalize.quantiles.in.blocksnormalize.quantiles.robustnormalize.quantiles.use.targetrcModelMedianPolishrcModelPLMrcModelPLMdrcModelPLMrrcModelPLMrcrcModelPLMrrrcModelWPLMrcModelWPLMrrcModelWPLMrcrcModelWPLMrrrma.background.correctsubColSummarizeAvgsubColSummarizeAvgLogsubColSummarizeBiweightsubColSummarizeBiweightLogsubColSummarizeLogAvgsubColSummarizeLogMediansubColSummarizeMediansubColSummarizeMedianLogsubColSummarizeMedianpolishsubColSummarizeMedianpolishLogsubrcModelMedianPolishsubrcModelPLM

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Summarize the columns of matricescolSummarizeAvg colSummarizeAvgLog colSummarizeBiweight colSummarizeBiweightLog colSummarizeLogAvg colSummarizeLogMedian colSummarizeMedian colSummarizeMedianLog colSummarizeMedianpolish colSummarizeMedianpolishLog
Quantile Normalizationnormalize.quantiles
Quantile Normalization carried out separately within blocks of rowsnormalize.quantiles.in.blocks
Robust Quantile Normalizationnormalize.AffyBatch.quantiles.robust normalize.quantiles.robust
Quantile Normalization using a specified target distribution vectornormalize.quantiles.determine.target normalize.quantiles.use.target
Fit row-column models with group-specific row effectsrcModelPLMd
Fit row-column models with row and/or column robustnessrcModelPLMr rcModelPLMrc rcModelPLMrr rcModelWPLMr rcModelWPLMrc rcModelWPLMrr
Fit additive row-column decomposition modelsrcModelMedianPolish rcModelPLM rcModelWPLM
RMA Background Correctionrma.background.correct
Summarize matrix columns by row groupsconvert.group.labels subColSummarizeAvg subColSummarizeAvgLog subColSummarizeBiweight subColSummarizeBiweightLog subColSummarizeLogAvg subColSummarizeLogMedian subColSummarizeMedian subColSummarizeMedianLog subColSummarizeMedianpolish subColSummarizeMedianpolishLog
Fit row-column model to a matrixsubrcModelMedianPolish subrcModelPLM subrcModelWPLM