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glmmSeq()
and lmmSeq()
glmmRefit()
...
in parallelisation on windows in
glmmSeq()
& lmmSeq()
glmmSeq()
to use glmmTMB
package for fitting negative binomial GLMM (or other GLM family)
modelsplab
argument to modelPlots
to
customise p-value labelsmeanExp
to results in
@stats$res
slotlmmSeq()
using
lme4::modular
code. Speed increase of around 25%.glmmSeq
and lmmSeq
summary
function for glmmSeq and lmmSeq to display
results for an individual gene@stats
slot in output objects to include
more information including DFlmmSeq
using the lmerTest
packagelmmRefit
function to fit an identical (g)lmer
model. This can then be passed to the emmeans
package for
visualisation of more complex models.modelPlots
(base graphics) and
ggmodelPlots
(ggplot2)modelPlots
to allow for simplest case
gene ~ Time + (1 | ID)
lmmSeq()
. Improves speed of calculation
of type 2 Wald test. Overall speed increase of 25-50%.glmmSeq()
id
column name from the RE term
in the formula...
option to fcPlot
which is passed
to plotly()
or ggplot()
annotationPosition=FALSE
in fcPlot
so
arrows/connectors are not movedreturnList
to return glmmSeq output as list
(to make error catching easier)glmmSeq
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.