Changelog
Source:NEWS.md
variancePartition 1.35.5
- June 17, 2024
- fix bug in
mvTest()
forse
value with 1 feature
variancePartition 1.35.3
- June 11, 2024
- in
mvTest()
withshrink.cov = TRUE
useslambda = 0.01
variancePartition 1.35.2
- June 6, 2024
- in
mvTest()
returnbeta
andse
variancePartition 1.33.15
- May 16, 2024
- in
voomWithDreamWeights()
, default changed torescaleWeightsAfter = FALSE
variancePartition 1.33.14
- April 19, 2024
- in
topTable()
resolve issue when specifying multiple coeffs
variancePartition 1.33.13
- April 6, 2024
- in
voomWithDreamWeights()
, add argumentprior.count.for.weights
variancePartition 1.33.12
- March 22, 2024
- Fix use with
voomWithDreamWeights()
taking raw counts - https://github.com/GabrielHoffman/variancePartition/issues/97
- in
voomWithDreamWeights()
, add argumentpriorWeightsAsCounts=FALSE
andprior.count.for.weights
variancePartition 1.33.11
- Feb 7, 2024
- fix bug in
dream(...,ddf="Kenward-Roger")
that gave false positives and negatives- scaled weights properly to fix this issue, since
df
inlmerTest::contest()
assumes mean of weights is 1. - old code used unscaled weights, so df values were too large
- scaled weights properly to fix this issue, since
variancePartition 1.33.10
- Feb 5, 2024
- in
augmentPriorCount()
andvoomWithDreamWeights()
, add argumentscaledByLib=FALSE
variancePartition 1.33.9
- Jan 25, 2024
- bug fix in
BIC()
and.fitExtractVarPartModel()
variancePartition 1.33.5
- Dec 21, 2023
- fix issue with ddf always calling
"Satterthwaite"
- enforce subsetting of residuals in
assign( "[.MArrayLM2",)
- this comes with when
rdf < 1
- this comes with when
variancePartition 1.33.4
- Dec 13, 2023
- fix bug with BiocParallel in Windows
- handle case where a single contrasts fails in
makeContrastsDream()
variancePartition 1.33.3
- Dec 5, 2023
- in
residuals()
when dividing bysqrt(1-hatvalues)
add small offset to make sure the value is positive
variancePartition 1.33.2
- Nov 13, 2023
- add
augmentPriorCount()
- add
prior.count
argument tovoomWithDreamWeights()
and feed it toaugmentPriorCount()
variancePartition 1.31.22
- Oct 19, 2023
- fix handling of variables with missing data
- return
fit$genes
properly
variancePartition 1.31.21
- Oct 16, 2023
- handle weights properly when the linear mixed model fails for some genes
-
lmFit()
and - in
iterRows()
setscale = FALSE
as default - in
voomWithDreamWeights()
, scale in input weights and weights in sidefitVarPartModel()
- get weights estimated most similar to
voomLmFit()
- get weights estimated most similar to
- in
dream()
userescaleWeights = FALSE
to getsigma
estimates compatable withlmFit()
variancePartition 1.31.20
- Sept 26, 2023
- allow
weights
to be a matrix invoomWithDreamWeights()
variancePartition 1.31.19
- Sept 22, 2023
- add
rescaleWeightsAfter
argument tovoomWithDreamWeights()
variancePartition 1.31.18
- Sept 5, 2023
- improved error handling for
fitVarPartModel()
,fitExtractVarPartModel()
, andvoomWithDreamWeights()
variancePartition 1.31.16
- August 18, 2023
- in
dream()
, if"Kenward-Roger"
is specified but gives covariance matrix that has poor condition number or is not positive definite, then fall back to"Satterthwaite"
for hypothesis testing in linear mixed models - Update documentation, and reformat code
variancePartition 1.31.15
- August 10, 2023
-
fit = dream()
now returnsfit$loglik
(the log-likelihood for each gene), andfit$edf
(the effective degreees of freedom for each gene)
variancePartition 1.31.13
- August 7, 2023
- fix bug in
calcVarPart()
where weights was ignored in some cases - add additional tests to check this
variancePartition 1.31.12
- July 3, 2023
-
makeContrastsDream()
convertsNA
contrasts
toNULL
variancePartition 1.31.11
- setting
voomWithDreamWeights(..., span="auto")
now estimates tuning parameter from data usingfANCOVA::loess.as()
variancePartition 1.31.9
- Fix issue in
mvTest()
when specifying features with strings
variancePartition 1.31.7
- update
mvTest()
to run in parallel
variancePartition 1.31.6
- update
mvTest()
to include Hotelling T2 test andLS.empirical()
variancePartition 2.0.5
- May 31, 2023
- fix convergence issues
- fix initialization of
lmer()
fit - use 1 OMP thread internally, then restore to original value
variancePartition 2.0.4
- May 30, 2023
- When running
dream()
, ensure model convergence using second fitting withNelder_Mead
to avoid edge cases where the approximate hessian fromlmerTest::as_lmerModLT()
has a negative eigenvalue - fix issue in
get_prediction()
returning NA values when variables modeled as categorical and levels are omitted - fix issue in
voomWithDreamWeights()
when some genes don’t converge - retry
lmer()
model fit with another optimizer after it fails convergence test.
variancePartition 2.0.3
- May 13, 2023
- fix
vcov()
variancePartition 2.0.2
- May 17, 2023
- add matrix argument to
mvTest()
variancePartition 2.0.1
- May 12, 2023
-
mvTest()
now shrinks covariance using the Schafer-Strimmer method -
vcovSqrt()
returns the matrix whose cross product gives thevcov()
result from fits withdream()
variancePartition 2.0.0
- April 20, 2023
- Major code refactoring to:
- improve code reuse
- simplify debugging and maintaining code
- simplify addition of new features
- improve error handling
- some linear mixed model analyses are 50% faster
- enable additional features for
dreamlet
package that depends heavily onvariancePartition
.
variancePartition 1.28.9
- March 14, 2023
- fix rounding error in
makeContrastsDream()
- add Pearson residuals to
residuals()
variancePartition 1.28.8
- March 8, 2023
- add
mvTest()
with features as list
variancePartition 1.28.7
- March 7, 2023
- Fix bug in
makeContrastsDream()
by addingdroplevels()
variancePartition 1.28.6
- March 1, 2023
-
diffVar()
now fits contrasts estimated in first step
variancePartition 1.28.5
- Feb 24, 2023
- Fix error in
vcov()
when samples are dropped due to covariate havingNA
value
variancePartition 1.28.2
- Jan 13, 2023
-
canCorPairs()
now allows random effects in formula- but won’t change results
variancePartition 1.27.17
- in
mvTest()
, more consistent return values when one features is used
variancePartition 1.27.14
- fix bug in
topTable()
- add
deviance()
- update docs
- update
sqrtMatrix()
to have positive diagonal
variancePartition 1.27.13
- add
diffVar()
test of differential variance -
dream()
now returnsformula
,data
, andhatvalues
- define
hatvalues()
for result ofdream()
variancePartition 1.27.12
- in
mvTest()
:- default method is now
"FE"
- default method is now
variancePartition 1.27.11
- in
mvTest()
:- return number of features
- return stat.FE and stat.het for RE2C
- return NA for stat if 1 feature
variancePartition 1.27.10
- Add check for very large weights in
voomWithDreamWeights()
- follows bug report: https://github.com/GabrielHoffman/variancePartition/issues/66
- in
mvTest()
change option “LS” to “FE”
variancePartition 1.27.8
- bug fix in
mvTest()
variancePartition 1.27.5
- update dependencies
- make
topTable()
generic to work with R 4.2.1 and Bioc 3.16
variancePartition 1.27.3
- update filtering of covariates, especially for when many samples are dropped
variancePartition 1.25.13
- Fix compatibility issue with lme4 1.1.29
- reported https://github.com/GabrielHoffman/variancePartition/issues/51
variancePartition 1.25.12
- in
makeContrastsDream()
, fix issue where terms with colon cause and error
variancePartition 1.25.11
- fix bug in
dream()
for variables with NA values - improve handling of invalid contrasts in
makeContrastsDream()
variancePartition 1.25.9
- for
getContrast()
andmakeContrastsDream()
make sure formula argument is a formula and not a string
variancePartition 1.25.7
-
dream()
now drops samples with missing data gracefully
variancePartition 1.25.6
- fix small plotting bug in
plotStratify()
andplotStratifyBy()
variancePartition 1.25.5
- add
getTreat()
to evaluatetreat()
/topTreat()
seamlessly on results ofdream()
variancePartition 1.25.3
- add genes argument to
plotPercentBars()
variancePartition 1.25.2
- change
plotPercentBars()
to use generic S4
variancePartition 1.25.1
- update handling of
weights
invoomWithDreamWeights()
and addapplyQualityWeights()
variancePartition 1.23.6
- update
calcVarPart()
with argumentscale=TRUE
allowing the user to disable scaling to fractions
variancePartition 1.23.5
- use
RhpcBLASctl::omp_set_num_threads(1)
to use only 1 OpenMP thread for linear algebra within each BiocParallel process - update
dream()
souseWeights=FALSE
works withlmFit()
variancePartition 1.23.4
- convert some warnings to errors
- add proper handling of weights to
voomWithDreamWeights()
variancePartition 1.23.2
- add flag to checkModelStatus() so warnings are thrown immediately
- fix export of as.data.frame
- fixed issues where messages were printed even if quiet=TRUE
variancePartition 1.21.10
- add suppressWarnings flag to makeContrastsDream()
- ensure that z.std is finite
variancePartition 1.21.8
- update dream vignette
- update documentation for makeContrastsDream()
- fix error in rdf_from_matrices() with eigen() failing
variancePartition 1.21.7
- Merge changes to contrast code: https://github.com/GabrielHoffman/variancePartition/pull/32
- Merge improvments to error checking: https://github.com/GabrielHoffman/variancePartition/pull/28
- New warning/error if variables in formula have missing data
- add
makeContrastsDream()
variancePartition 1.21.4
- variance fractions for fixed effects model is now computed using new method
- fixes subtle issue with previous version where estimates dependend on of terms in the formula
- https://github.com/GabrielHoffman/variancePartition/issues/30
- Update documentation
variancePartition 1.21.3
- Faster aggregration after running multiple threads
- Pulled from https://github.com/GabrielHoffman/variancePartition/pull/27
- by Ryan C. Thompson
- eBayes() now works with dream for linear mixed models
- add rdf.merMod
variancePartition 1.21.2
- Reduce size of data passed to each thread by only including variables used in the formula. Applies to multiple functions
- add more unit tests
variancePartition 1.19.20
- fix bug discovered when the number of features is less than the number of chunks in iterBatch()
variancePartition 1.19.18
- simplify calcVarPart for lm and lmer. Add compatibility for glm
- Simplify checkModelStatus.merMod to allow formula (A|B) where A is continuous
- remove unused “adjust” arguments for clarity
variancePartition 1.19.17
- add get_prediction() for results of lm()
- improve documentation of get_prediction()
variancePartition 1.19.16
- in canCorPairs() change statistic used to summarize CCA to Cramer’s V. The difference is very subtle, but is now based on first principles.
- in dream, check that data is a data.frame
- dream() defaults to computeResiduals=TRUE for compatability with zenith
variancePartition 1.19.13
- fix issues with residuals()
- https://github.com/GabrielHoffman/variancePartition/issues/18
- fix issue exporting eBayes, topTable, etc
variancePartition 1.19.12
- Improve documentation for contrasts in dream.Rmd
- check that contrasts sum to zero in plotContrasts.
variancePartition 1.19.11
- in voomWithDreamWeights() fix issue with not defining design
- https://github.com/GabrielHoffman/variancePartition/issues/17
variancePartition 1.19.10
- in voomWithDreamWeights() fix issue with returning design matrix
- better error if counts can’t be converted to matrix
- https://github.com/GabrielHoffman/variancePartition/issues/15
variancePartition 1.19.7
- Round numbers in plotContrasts()
- fix issues with strings are passed to formula arguments
variancePartition 1.19.6
- New gives meaning full error message for dream(), etc when variable is not found in data.
variancePartition 1.19.5
- Better error catching when running fitVarPartModel() with fxn that fails
- add get_prediction() function
- the following code now can be run in parallel fitList = fitVarPartModel( Y, ~ (1|Batch), data, fxn = function(fit){ B = variancePartition::get_prediction(fit, ~(1|Batch)) fit@resp$y - B }, BPPARAM=SnowParam(3))
variancePartition 1.19.4
- Update vignette #3, and update documentation of REML argument
variancePartition 1.19.2
- canCorPairs() now returns NA correlation when two variables have no overlapping observed values
- plotCorrMatrix() now handles NA correlation values
variancePartition 1.18.1
- Clean up some code and add documentation
- compute effective degrees of freedom for each model
variancePartition 1.17.10
- fix issue returning residuals from limma
- resolve issue where dream gives error: r[cbind(1L:p, 1L:p)] <- 1 : subscript out of bounds
- only occured when no fixed effects were used
variancePartition 1.17.4
- Don’t print warnings for residuals() when only one argument passed.
- fix bug with residuals evaluated with only fixed effects
variancePartition 1.17.3
- Allow sparseMatrix for gene expression. Now saves memory by avoiding conversion to matrix. Processing sparseMatrix will be slower, but memory usage will be low.
- dream(…, computeResiduals=TRUE) now computes residuals and allows use of residuals() function
variancePartition 1.17.1
- topTable(…,sort.by=) now is correct when and F-test is used
- fixed issue in classifyTestsF.MArrayLM2, now is much faster
variancePartition 1.15.8
- Replace cat() with message()
- add quiet option to a few functions
- dream() does not call eBayes() when lmFit is used
variancePartition 1.15.6
- fix convergence errror when recycling parameters values from first gene
- add column z.std and F.std to topTable
variancePartition 1.13.8
- apply empirical Bayes when doing F-test
- hypothesis testing for single coefficients is now included by default, so only need to specify contrast matrix if for more complicated contrasts
- add voomWithDreamWeights() for computing observation weights using random effects
- Add BiocParallel capability with BPPARAM argument
- allows parallel processing with lower memory usage
- dream() is now compatable with gene set enrichments from pinnacle (software comming soon)
variancePartition 1.13.7
- in dream(), add support for genes annotation in DGElist()
- in dream(), automatically evaluate contrasts for all single coefficients
- add future compatability for gene set enrichments method “pinnacle”
variancePartition 1.13.4
- export classes to fix bug with class “varPartResults” not being defined
- Thanks Megan Behringer
variancePartition 1.13.2
- Enable random slope models in dream, but not for estimating variance fractions
- Thanks Jonas Zierer
variancePartition 1.11.8
- Check and stop() if response variable has variance of 0
- in dream(), fitExtractVarPartModel(), and fitVarPartModel()
- add standardized_t_stat() implicitly in eBayes() using MArrayLM2 class
- this transforms moderated t-statistics to have same degrees of freedom
variancePartition 1.11.7
- Simplify object return by dream to be more more similar to lmFit
- now returns MArrayLM instead of MArrayLMM_lmer
- if a fixed effects formula is specified (i.e. not random terms)
- dream call lmFit in the backend
- getContrast() works seamlessly
- dream() now returns gene annotation if passed to function
variancePartition 1.11.6
- add error checing for L in dream
- fix typoes in dream vignette
- fix typoes in theory_practice_random_effects.Rnw
variancePartition 1.11.5
- Add dream function for differential expression for repeated measures with a linear mixed model
variancePartition 1.5.5
- Decrease computing time of effective sample size with ESS() by additional ~10x with sparse solver
- fix margins for plotPercentBars()
- Fix bug for getVarianceComponents() when correlated continous variables are included
- compatibility with ggplot2 2.2.0
- center plot titles
- fix order of bars in plotPercentBars()
- legend background to transparent
- set text to be black
- include lme4 in foreach .packages
- change residuals color to not be transparent
- add CITATION information
- plotCorrMatrix now shows dendrogram by default
- Estimate run time for fitExtractVarPartModel() / fitVarPartModel()
- improve warnings for plotPercentBar()
- improve warnings for plotCorrStructure()
- define ylab for plotVarPart()
- add as.matrix.varPartResults() (hidden)
- define isVaryingCoefficientModel() (hidden)
variancePartition 1.3.11
- in canCorPairs() and other functions, convert formula with as.formula()
- improve error messages for canCorPairs()
variancePartition 1.3.8
- Add additional examples to vignette
- show projected memory usage of fitVarPartModel()
variancePartition 1.3.7
- fitVarPartModel warns if names in exprObj and data are not identical
- residuals() and other functions deal with missing values properly
variancePartition 1.1.9
- Update sortCols to handle Measurement.error
- change backend package structure
- set Residuals to be grey by default in plotVarPart() and plotPercentBars()
- add control = lme4::lmerControl(calc.derivs=FALSE, check.rankX=“stop.deficient” )
- add plotCorrStructure
variancePartition 1.1.8
- Add ESS.R
- Add fitVarTest.R
- use lmerTest by default
- fix bug checkModelStatus() for variables with backticks in name
variancePartition 1.1.6
- Move packages from Depends to Imports
- For clarity, replace = with <- in parts of examples and vignette
- Stop cluster in examples to solve error on Windows machines
variancePartition 1.1.1
- add plotPercentBars() to vizualize variance fractions for a subset of genes
- add ESS() to compute effective sample size
- fix x.labels argument in plotStratifyBy(). Previously, this argument was not used correctly
variancePartition 0.99.9
- add legend argument to plotStratifyBy()
- improve warnings / errors for varying coefficient models
- allow user to manually adjust cutoff for determining when design matrix is singular
- changed default cutoff to 0.999 from 0.99
variancePartition 0.99.8
- improve warnings / errors when design matrix is close to or exactly singular
variancePartition 0.99.7
- added new class varPartResults to store results of fitExtractVarPartModel() and extractVarPart()
- the user will not notice any change, only the backend is different o Allow computation of adjusted ICC in addition to ICC.
- add warning when categorical variables are modeled as fixed effects
- fix computation of variance fractions for varying coefficient models
- add getVarianceComponents() to return variances from lmer() or lm() model fit
- showWarnings=FALSE suppresses warning messages
- add fxn argument to fitVarPartModel to evaluate any function on the model fit
variancePartition 0.99.2
- rename sort.varParFrac to sortCols
- support ExpressionSet
- change options for plotStratifyBy()
variancePartition 0.0.10
- fitExtractVarPartModel() and fitVarPartModel() now take subset argument
- throw warning when no Intercept is specified
- if using lmer, warning if categorical variable is modeled as fixed effect
- fixed calcVarPart bug with reporting too few variances for multicategory fixed effects
- add colinearityScore
variancePartition 0.0.9
- remove warning about unspecified weights, when useWeights=TRUE
- fix issue with sort with only one variable
- add main argument to plotVarPart
variancePartition 0.0.6
- set REML=FALSE to default. This fixes issues of inaccurate variance estiamtes, and makes lmer() results more concordant with lm() results
- Fix residuals function when lm or lmer is used
- fix useWeights argument error for fitExtractVarPartModel()