Package: preprocessCore 1.69.0

Ben Bolstad

preprocessCore: A collection of pre-processing functions

A library of core preprocessing routines.

Authors:Ben Bolstad <[email protected]>

preprocessCore_1.69.0.tar.gz
preprocessCore_1.69.0.zip(r-4.5)preprocessCore_1.69.0.zip(r-4.4)preprocessCore_1.69.0.zip(r-4.3)
preprocessCore_1.69.0.tgz(r-4.5-x86_64)preprocessCore_1.69.0.tgz(r-4.5-arm64)preprocessCore_1.69.0.tgz(r-4.4-x86_64)preprocessCore_1.69.0.tgz(r-4.4-arm64)preprocessCore_1.69.0.tgz(r-4.3-x86_64)preprocessCore_1.69.0.tgz(r-4.3-arm64)
preprocessCore_1.69.0.tar.gz(r-4.5-noble)preprocessCore_1.69.0.tar.gz(r-4.4-noble)
preprocessCore_1.69.0.tgz(r-4.4-emscripten)preprocessCore_1.69.0.tgz(r-4.3-emscripten)
preprocessCore.pdf |preprocessCore.html
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-1.69.0(bioc 3.21)preprocessCore-1.68.0(bioc 3.20)

infrastructureopenblas

12.03 score 19 stars 204 packages 1.8k scripts 21k downloads 146 mentions 39 exports 0 dependencies

Last updated 4 months agofrom:d2e67f1e83. Checks:1 OK, 1 ERROR, 9 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 28 2025
R-4.5-win-x86_64WARNINGFeb 28 2025
R-4.5-mac-x86_64WARNINGFeb 28 2025
R-4.5-mac-aarch64WARNINGFeb 28 2025
R-4.5-linux-x86_64ERRORFeb 28 2025
R-4.4-win-x86_64WARNINGFeb 28 2025
R-4.4-mac-x86_64WARNINGFeb 28 2025
R-4.4-mac-aarch64WARNINGFeb 28 2025
R-4.3-win-x86_64WARNINGFeb 28 2025
R-4.3-mac-x86_64WARNINGFeb 28 2025
R-4.3-mac-aarch64WARNINGFeb 28 2025

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