| subsetSamples {MOFA} | R Documentation |
Method to subset (or sort) samples.
This function can remove samples from the model. For example,
you might want to observe the effect of Factor 1 on a subset of samples.
You can create a new MOFAmodel excluding some samples
and then visualise the effect of Factor 1 on the remaining ones, for instance via
plotDataHeatmap or plotFactorScatter.
This functionality is only for exploratory purposes.
In the case of outliers, we strongly recommend removing them before training the model.
subsetSamples(object, samples)
object |
a |
samples |
character vector with the sample names, numeric vector with the sample indices or logical vector with the samples to be kept as TRUE. |
MOFAmodel object with a subset of samples
# Using an existing trained model on the CLL data
filepath <- system.file("extdata", "CLL_model.hdf5", package = "MOFAdata")
MOFA_CLL <- loadModel(filepath)
# Subset samples via character vector
MOFA_CLL_small <- subsetSamples(MOFA_CLL, samples=c("H045","H109","H024","H056"))
MOFA_CLL_small
# Subset samples via numeric vector
MOFA_CLL_small <- subsetSamples(MOFA_CLL, samples=1:10)
MOFA_CLL_small