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variancePartition

Quantify and interpret divers 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.

Functions (46)

ESS-method

Effective sample size

FMT

Fully moderated t-test

FMT-class

Class FMT

FMT.ZI

Fully moderated t-test for zero-inflated variances

MArrayLM2-class

Class MArrayLM2

VarParCIList-class

Class VarParCIList

VarParFitList-class

Class VarParFitList

as.data.frame-varPartResults-method

Convert to data.frame

as.matrix-varPartResults-method

Convert to matrix

calcVarPart-method

Compute variance statistics

canCorPairs

canCorPairs

classifyTestsF

Multiple Testing Genewise Across Contrasts

classifyTestsF-MArrayLM2-method

Multiple Testing Genewise Across Contrasts

colinearityScore

Collinearity score

dot-getAllUniContrasts

Get all univariate contrasts

dot-isMixedModelFormula

Check if model contains a random effect

dot-standard_transform

Compute standard post-processing values

dream-method

Differential expression with linear mixed model

eBayes-method

eBayes for MArrayLM2

eBayesFMT

Empirical Bayes Fully Moderated t-statistics

extractVarPart

Extract variance statistics

fitExtractVarPartModel-method

Fit linear (mixed) model, report variance fractions

fitVarPartModel-method

Fit linear (mixed) model

getContrast-method

Extract contrast matrix for linear mixed model

get_prediction-method

Compute predicted value of formula for linear (mixed) model

ggColorHue

Default colors for ggplot

plotCompareP-method

Compare p-values from two analyses

plotContrasts

Plot representation of contrast matrix

plotCorrMatrix

plotCorrMatrix

plotCorrStructure

plotCorrStructure

plotPercentBars

Bar plot of variance fractions

plotStratify

plotStratify

plotStratifyBy

plotStratifyBy

plotVarPart-method

Violin plot of variance fractions

residuals-MArrayLM-method

residuals for MArrayLM

residuals-MArrayLM2-method

residuals for MArrayLM2

residuals-VarParFitList-method

Residuals from model fit

sortCols-method

Sort variance partition statistics

subset.MArrayLM2-method

Subseting for MArrayLM2

toptable-method

toptable for definition

varParFrac-class

Class varParFrac

varPartConfInf

Linear mixed model confidence intervals

varPartDEdata

Simulation dataset for dream example

varPartData

Simulation dataset for examples

varPartResults-class

Class varPartResults

voomWithDreamWeights

Transform RNA-Seq Data Ready for Linear Mixed Modelling with dream()

variancePartition

Quantify and interpret divers of variation in multilevel gene expression experiments

v1.20.0
GPL (>= 2)
Authors
Gabriel E. Hoffman
Initial release
2020-10-26

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