Package: variancePartition 1.37.1
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:
variancePartition_1.37.1.tar.gz
variancePartition_1.37.1.zip(r-4.5)variancePartition_1.37.1.zip(r-4.4)variancePartition_1.37.1.zip(r-4.3)
variancePartition_1.37.1.tgz(r-4.4-any)variancePartition_1.37.1.tgz(r-4.3-any)
variancePartition_1.37.1.tar.gz(r-4.5-noble)variancePartition_1.37.1.tar.gz(r-4.4-noble)
variancePartition_1.37.1.tgz(r-4.4-emscripten)variancePartition_1.37.1.tgz(r-4.3-emscripten)
variancePartition.pdf |variancePartition.html✨
variancePartition/json (API)
NEWS
| # 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:https://diseaseneurogenomics.github.io
- 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-1.37.1(bioc 3.21)variancePartition-1.36.2(bioc 3.20)
rnaseqgeneexpressiongenesetenrichmentdifferentialexpressionbatcheffectqualitycontrolregressionepigeneticsfunctionalgenomicstranscriptomicsnormalizationpreprocessingmicroarrayimmunooncologysoftware
Last updated 1 months agofrom:f3d77115cc. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 13 2024 |
| R-4.5-win | WARNING | Dec 13 2024 |
| R-4.5-linux | WARNING | Dec 13 2024 |
| R-4.4-win | WARNING | Dec 13 2024 |
| R-4.4-mac | WARNING | Dec 13 2024 |
| R-4.3-win | WARNING | Dec 13 2024 |
| R-4.3-mac | WARNING | Dec 13 2024 |
Exports:[.MArrayLM2applyQualityWeightsas.matrixaugmentPriorCountcalcVarPartcanCorPairscolinearityScoredeviationdiffVardreameBayesESSextractVarPartfitExtractVarPartModelfitVarPartModelget_predictiongetContrastgetTreatggColorHuehatvaluesisRunableFormulamakeContrastsDreammvTestplotComparePplotContrastsplotCorrMatrixplotCorrStructureplotPercentBarsplotStratifyplotStratifyByplotVarianceEstimatesplotVarPartrdfrdf.merModresidualsresiduals.MArrayLM2shrinkageMetricsortColstopTablevarPartConfInfvcovvcovSqrtvoomWithDreamWeights
Dependencies:aodbackportsBHBiobaseBiocGenericsBiocParallelbitopsbootbroomcaToolsclicodetoolscolorspacecorpcorcowplotcpp11DerivdoBydplyrEnvStatsfANCOVAfansifarverformatRfutile.loggerfutile.optionsgenericsggplot2gluegplotsgtablegtoolsisobanditeratorsKernSmoothlabelinglambda.rlatticelifecyclelimmalme4lmerTestmagrittrMASSMatrixmatrixStatsmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnortestnumDerivpbkrtestpillarpkgconfigplyrpurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackremaCorreshape2RhpcBLASctlrlangscalessnowstatmodstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Variance partitioning analysis
Rendered fromvariancePartition.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2023-08-18
Started: 2023-08-18
Additional visualizations of variance structure
Rendered fromadditional_visualization.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2023-08-18
Started: 2019-07-08
Theory and practice of random effects
Rendered fromrnd_effects.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2023-08-18
Started: 2023-06-21
dream analysis
Rendered fromdream.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2024-05-31
Started: 2018-06-11
Error handling
Rendered fromerrors.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2023-09-05
Started: 2023-08-18
Frequently asked questions
Rendered fromFAQ.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2023-09-05
Started: 2020-06-13
Multivariate tests
Rendered frommvtests.Rmdusingknitr::rmarkdownon Dec 13 2024.Last update: 2023-09-05
Started: 2023-06-21
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Apply pre-specified sample weights | applyQualityWeights |
| Convert to data.frame | as.data.frame.varPartResults |
| Convert to matrix | as.matrix as.matrix,varPartResults-method |
| Augment observed read counts with prior count | augmentPriorCount |
| BIC from model fit | BIC.MArrayLM |
| BIC from model fit | BIC.MArrayLM2 |
| Compute variance statistics | calcVarPart calcVarPart,glm-method calcVarPart,glmer-method calcVarPart,glmerMod-method calcVarPart,lm-method calcVarPart,lmerMod-method calcVarPart,negbin-method |
| canCorPairs | canCorPairs |
| Multiple Testing Genewise Across Contrasts | classifyTestsF |
| Multiple Testing Genewise Across Contrasts | classifyTestsF,MArrayLM2-method |
| Collinearity score | colinearityScore |
| Deviation from expectation for each observation | deviation deviation,MArrayLM-method |
| Test differential variance | diffVar diffVar,MArrayLM-method |
| Differential expression with linear mixed model | dream |
| Scaled chi-square | dscchisq |
| eBayes for MArrayLM2 | eBayes,MArrayLM2-method |
| Effective sample size | ESS ESS,lmerMod-method |
| Extract variance statistics | extractVarPart |
| Fit linear (mixed) model, report variance fractions | fitExtractVarPartModel fitExtractVarPartModel,data.frame-method fitExtractVarPartModel,EList-method fitExtractVarPartModel,ExpressionSet-method fitExtractVarPartModel,matrix-method fitExtractVarPartModel,sparseMatrix-method |
| Fit linear (mixed) model | fitVarPartModel fitVarPartModel,data.frame-method fitVarPartModel,EList-method fitVarPartModel,ExpressionSet-method fitVarPartModel,matrix-method fitVarPartModel,sparseMatrix-method |
| Compute predicted value of formula for linear (mixed) model | get_prediction get_prediction,lm-method get_prediction,lmerMod-method |
| Extract contrast matrix for linear mixed model | getContrast |
| Test if coefficient is different from a specified value | getTreat getTreat,MArrayLM-method getTreat,MArrayLM2-method |
| Default colors for ggplot | ggColorHue |
| Compute hatvalues | hatvalues,MArrayLM-method hatvalues,MArrayLM2-method |
| Test if formula is full rank on this dataset | isRunableFormula |
| Log-likelihood from model fit | logLik.MArrayLM |
| Log-likelihood from model fit | logLik.MArrayLM2 |
| Construct Matrix of Custom Contrasts | makeContrastsDream |
| Class MArrayLM2 | MArrayLM2-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_input | mvTest_input-class |
| Compare p-values from two analyses | plotCompareP |
| Plot representation of contrast matrix | plotContrasts |
| plotCorrMatrix | plotCorrMatrix |
| plotCorrStructure | plotCorrStructure |
| Bar plot of gene fractions | plotPercentBars plotPercentBars,data.frame-method plotPercentBars,matrix-method plotPercentBars,varPartResults-method |
| plotStratify | plotStratify |
| plotStratifyBy | plotStratifyBy |
| Plot Variance Estimates | plotVarianceEstimates |
| Violin plot of variance fractions | plotVarPart plotVarPart,data.frame-method plotVarPart,matrix-method plotVarPart,varPartResults-method |
| Residual degrees of freedom | rdf |
| Fast approximate residual degrees of freedom | rdf_from_matrices |
| Approximate residual degrees of freedom | rdf.merMod |
| Adapted from lme4:::reOnly | reOnly |
| residuals for MArrayLM | residuals,MArrayLM-method |
| residuals for MArrayLM2 | residuals,MArrayLM2-method |
| Residuals from model fit | residuals,VarParFitList-method |
| Residuals for result of dream | residuals.MArrayLM2 |
| Shrinkage metric for eBayes | shrinkageMetric |
| Sort variance partition statistics | sortCols sortCols,data.frame-method sortCols,matrix-method sortCols,varPartResults-method |
| Table of Top Genes from Linear Model Fit | topTable topTable,MArrayLM-method toptable,MArrayLM-method topTable,MArrayLM2-method toptable,MArrayLM2-method |
| Class VarParCIList | VarParCIList-class |
| Class VarParFitList | VarParFitList-class |
| Class varParFrac | varParFrac-class |
| Linear mixed model confidence intervals | varPartConfInf |
| Simulation dataset for examples | geneCounts geneExpr info varPartData |
| A simulated dataset of gene counts | countMatrix metadata varPartDEdata |
| Class varPartResults | varPartResults-class |
| Co-variance matrix for 'dream()' fit | vcov,MArrayLM-method |
| Co-variance matrix for 'dream()' fit | vcov,MArrayLM2-method |
| Sqrt of co-variance matrix for 'dream()' fit | mvTest,MArrayLM-method mvTest,MArrayLM2-method vcovSqrt vcovSqrt,MArrayLM-method vcovSqrt,MArrayLM2-method |
| Transform RNA-Seq Data Ready for Linear Mixed Modelling with 'dream()' | voomWithDreamWeights |
