Package: variancePartition 1.43.1

Gabriel E. Hoffman

variancePartition: Quantify and interpret drivers of variation in multilevel gene expression experiments

Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.

Authors:Gabriel Hoffman [aut, cre]

variancePartition_1.43.1.tar.gz
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manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
variancePartition/json (API)

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

Bug tracker:https://github.com/diseaseneurogenomics/variancepartition/issues

Pkgdown/docs site:https://diseaseneurogenomics.github.io

Datasets:
  • countMatrix - A simulated dataset of gene counts
  • geneCounts - Simulation dataset for examples
  • geneExpr - Simulation dataset for examples
  • info - Simulation dataset for examples
  • metadata - A simulated dataset of gene counts

On BioConductor:variancePartition-1.43.1(bioc 3.24)variancePartition-1.42.0(bioc 3.23)

rnaseqgeneexpressiongenesetenrichmentdifferentialexpressionbatcheffectqualitycontrolregressionepigeneticsfunctionalgenomicstranscriptomicsnormalizationpreprocessingmicroarrayimmunooncologysoftware

12.67 score 16 stars 6 packages 1.5k scripts 2.2k downloads 25 mentions 43 exports 90 dependencies

Last updated from:97c8bfeab0. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

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linux-release-x86_64NOTE606
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wasm-releaseOK222

Exports:[.MArrayLM2applyQualityWeightsas.matrixaugmentPriorCountcalcVarPartcanCorPairscolinearityScoredeviationdiffVardreameBayesESSextractVarPartfitExtractVarPartModelfitVarPartModelget_predictiongetContrastgetTreatggColorHuehatvaluesisRunableFormulamakeContrastsDreammvTestplotComparePplotContrastsplotCorrMatrixplotCorrStructureplotPercentBarsplotStratifyplotStratifyByplotVarianceEstimatesplotVarPartrdfrdf.merModresidualsresiduals.MArrayLM2shrinkageMetricsortColstopTablevarPartConfInfvcovvcovSqrtvoomWithDreamWeights

Dependencies:aodbackportsBHBiobaseBiocGenericsBiocParallelbitopsbootbroomcaToolsclicodetoolscolorspacecorpcorcowplotcpp11DerivdoBydplyrEnvStatsfANCOVAfarverforecastformatRfracdifffutile.loggerfutile.optionsgenericsggplot2gluegplotsgtablegtoolsisobanditeratorsKernSmoothlabelinglambda.rlatticelifecyclelimmalme4lmerTestlmtestmagrittrMASSMatrixmatrixStatsmicrobenchmarkminqamodelrmvtnormnlmenloptrnnetnortestnumDerivpbkrtestpillarpkgconfigplyrpurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasremaCorreshape2RhpcBLASctlrlangS7scalessnowstatmodstringistringrtibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Variance partitioning analysis
Introduction | Input data | Running an analysis | Standard application | Saving plot to file | Plot expression stratified by other variables | Intuition about the backend | Interpretation | Should a variable be modeled as fixed or random effect? | Which variables should be included? | Assess correlation between all pairs of variables | Advanced analysis | Extracting additional information from model fits | Removing batch effects before fitting model | Variation within multiple subsets of the data | Detecting problems caused by collinearity of variables | Including weights computed separately | Including interaction terms | Application to expression data | Gene-level counts | limma::voom() | DESeq2 | Isoform quantification | tximport | Compare with other methods | Tissue is major source of variation | Individual is major source of variation | Statistical details | Implementation in R | Interpretation of percent variance explained | Variation with multiple subsets of the data | Variance partitioning and differential expression | Modelling error in gene expression measurements | Session Info | References

Last update: 2026-05-11
Started: 2023-08-18

dream analysis
Standard RNA-seq processing | Limma Analysis | Dream Analysis | Advanced hypothesis testing | Using contrasts to compare coefficients | Comparing multiple coefficients | Joint hypothesis test of multiple coefficients | Small-sample method | variancePartition plot | Comparing p-values | Parallel processing | Session info | References

Last update: 2024-05-31
Started: 2018-06-11

Error handling
Errors in dream() | Gene-level errors | Shared by multiple functions | Warnings | Errors | Errors: Problems removing samples with NA/NaN/Inf values | Errors with BiocParallel multithreading backend | globally specify that all multithreading using bpiterate from BiocParallel | should use 8 cores | Session Info

Last update: 2023-09-05
Started: 2023-08-18

Frequently asked questions
Interperting the residual variance | Current GitHub issues | Session Info

Last update: 2023-09-05
Started: 2020-06-13

Multivariate tests
Import transcript-level counts | Standard dream analysis | Multivariate analysis | Gene set analysis | Session info | References

Last update: 2023-09-05
Started: 2023-06-21

Additional visualizations of variance structure
Plot variance structure | By Individual | Reorder samples | Original order of samples | By Tissue | By Individual and Tissue | Session Info

Last update: 2023-08-18
Started: 2019-07-08

Theory and practice of random effects
variancePartition | Estimating contributions to expression variation | dream | Hypothesis testing | Session Info

Last update: 2023-08-18
Started: 2023-06-21

Readme and manuals

Help Manual

Help pageTopics
Apply pre-specified sample weightsapplyQualityWeights
Convert to data.frameas.data.frame.varPartResults
Convert to matrixas.matrix as.matrix,varPartResults-method
Augment observed read counts with prior countaugmentPriorCount
BIC from model fitBIC.MArrayLM
BIC from model fitBIC.MArrayLM2
Compute variance statisticscalcVarPart calcVarPart,glm-method calcVarPart,glmer-method calcVarPart,glmerMod-method calcVarPart,lm-method calcVarPart,lmerMod-method calcVarPart,negbin-method
canCorPairscanCorPairs
Multiple Testing Genewise Across ContrastsclassifyTestsF
Multiple Testing Genewise Across ContrastsclassifyTestsF,MArrayLM2-method
Collinearity scorecolinearityScore
Deviation from expectation for each observationdeviation deviation,MArrayLM-method
Test differential variancediffVar diffVar,MArrayLM-method
Differential expression with linear mixed modeldream
Scaled chi-squaredscchisq
eBayes generic for for MArrayLM and MArrayLM2eBayes
eBayes for MArrayLMeBayes,MArrayLM-method
eBayes for MArrayLM2eBayes,MArrayLM2-method
Effective sample sizeESS ESS,lmerMod-method
Extract variance statisticsextractVarPart
Fit linear (mixed) model, report variance fractionsfitExtractVarPartModel fitExtractVarPartModel,data.frame-method fitExtractVarPartModel,EList-method fitExtractVarPartModel,ExpressionSet-method fitExtractVarPartModel,matrix-method fitExtractVarPartModel,sparseMatrix-method
Fit linear (mixed) modelfitVarPartModel fitVarPartModel,data.frame-method fitVarPartModel,EList-method fitVarPartModel,ExpressionSet-method fitVarPartModel,matrix-method fitVarPartModel,sparseMatrix-method
Compute predicted value of formula for linear (mixed) modelget_prediction get_prediction,lm-method get_prediction,lmerMod-method
Extract contrast matrix for linear mixed modelgetContrast
Test if coefficient is different from a specified valuegetTreat getTreat,MArrayLM-method getTreat,MArrayLM2-method
Default colors for ggplotggColorHue
Compute hatvalueshatvalues,MArrayLM-method hatvalues,MArrayLM2-method
Test if formula is full rank on this datasetisRunableFormula
Log-likelihood from model fitlogLik.MArrayLM
Log-likelihood from model fitlogLik.MArrayLM2
Construct Matrix of Custom ContrastsmakeContrastsDream
Class MArrayLM2MArrayLM2-class
Multivariate tests on results from 'dream()'mvTest mvTest,MArrayLM,EList,integer-method mvTest,MArrayLM,EList,list-method mvTest,MArrayLM,EList,missing-method mvTest,MArrayLM,EList,vector-method mvTest,MArrayLM,matrix,ANY-method mvTest,MArrayLM,matrix-method mvTest,mvTest_input,ANY,ANY-method mvTest,mvTest_input,method
Class mvTest_inputmvTest_input-class
Compare p-values from two analysesplotCompareP
Plot representation of contrast matrixplotContrasts
plotCorrMatrixplotCorrMatrix
plotCorrStructureplotCorrStructure
Bar plot of gene fractionsplotPercentBars plotPercentBars,data.frame-method plotPercentBars,matrix-method plotPercentBars,varPartResults-method
plotStratifyplotStratify
plotStratifyByplotStratifyBy
Plot Variance EstimatesplotVarianceEstimates
Violin plot of variance fractionsplotVarPart plotVarPart,data.frame-method plotVarPart,matrix-method plotVarPart,varPartResults-method
Residual degrees of freedomrdf
Fast approximate residual degrees of freedomrdf_from_matrices
Approximate residual degrees of freedomrdf.merMod
Adapted from lme4:::reOnlyreOnly
residuals for MArrayLMresiduals,MArrayLM-method
residuals for MArrayLM2residuals,MArrayLM2-method
Residuals from model fitresiduals,VarParFitList-method
Residuals for result of dreamresiduals.MArrayLM2
Shrinkage metric for eBayesshrinkageMetric
Sort variance partition statisticssortCols sortCols,data.frame-method sortCols,matrix-method sortCols,varPartResults-method
Table of Top Genes from Linear Model FittopTable topTable,MArrayLM-method toptable,MArrayLM-method topTable,MArrayLM2-method toptable,MArrayLM2-method
Class VarParCIListVarParCIList-class
Class VarParFitListVarParFitList-class
Class varParFracvarParFrac-class
Linear mixed model confidence intervalsvarPartConfInf
Simulation dataset for examplesgeneCounts geneExpr info varPartData
A simulated dataset of gene countscountMatrix metadata varPartDEdata
Class varPartResultsvarPartResults-class
Co-variance matrix for 'dream()' fitvcov,MArrayLM-method
Co-variance matrix for 'dream()' fitvcov,MArrayLM2-method
Sqrt of co-variance matrix for 'dream()' fitmvTest,MArrayLM-method mvTest,MArrayLM2-method vcovSqrt vcovSqrt,MArrayLM-method vcovSqrt,MArrayLM2-method
Transform RNA-Seq Data Ready for Linear Mixed Modelling with 'dream()'voomWithDreamWeights