Package: preprocessCore 1.75.0

Ben Bolstad

preprocessCore: A collection of pre-processing functions

A library of core preprocessing routines.

Authors:Ben Bolstad <[email protected]>

preprocessCore_1.75.0.tar.gz
preprocessCore_1.75.0.zip(r-4.7-x86_64)preprocessCore_1.75.0.zip(r-4.7-arm64)preprocessCore_1.75.0.zip(r-4.6-x86_64)preprocessCore_1.75.0.zip(r-4.6-arm64)preprocessCore_1.75.0.zip(r-4.5-x86_64)
preprocessCore_1.75.0.tgz(r-4.6-x86_64)preprocessCore_1.75.0.tgz(r-4.6-arm64)preprocessCore_1.75.0.tgz(r-4.5-x86_64)preprocessCore_1.75.0.tgz(r-4.5-arm64)
preprocessCore_1.75.0.tar.gz(r-4.7-arm64)preprocessCore_1.75.0.tar.gz(r-4.7-x86_64)preprocessCore_1.75.0.tar.gz(r-4.6-arm64)preprocessCore_1.75.0.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-1.75.0(bioc 3.24)preprocessCore-1.74.0(bioc 3.23)

infrastructureopenblas

12.11 score 19 stars 216 packages 2.8k scripts 24k downloads 146 mentions 39 exports 0 dependencies

Last updated from:4e5bfc285f. Checks:1 ERROR, 13 WARNING, 1 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR138
linux-devel-arm64WARNING99
linux-devel-x86_64WARNING189
source / vignettesOK203
linux-release-arm64WARNING161
linux-release-x86_64WARNING197
macos-release-arm64WARNING84
macos-release-x86_64WARNING285
macos-oldrel-arm64WARNING103
macos-oldrel-x86_64WARNING267
windows-devel-arm64WARNING180
windows-devel-x86_64WARNING92
windows-release-arm64WARNING165
windows-release-x86_64WARNING69
windows-oldrel-x86_64WARNING88
wasm-releaseFAIL104

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 column 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 robust row-column models to a matrixrcModelPLMd
Fit robust row-column models to a matrixrcModelPLMr rcModelPLMrc rcModelPLMrr rcModelWPLMr rcModelWPLMrc rcModelWPLMrr
Fit row-column model to a matrixrcModelMedianPolish rcModelPLM rcModelWPLM
RMA Background Correctionrma.background.correct
Summarize columns when divided into groups of rowsconvert.group.labels subColSummarizeAvg subColSummarizeAvgLog subColSummarizeBiweight subColSummarizeBiweightLog subColSummarizeLogAvg subColSummarizeLogMedian subColSummarizeMedian subColSummarizeMedianLog subColSummarizeMedianpolish subColSummarizeMedianpolishLog
Fit row-column model to a matrixsubrcModelMedianPolish subrcModelPLM subrcModelWPLM