subsetSamples {MOFA} | R Documentation

## Subset samples

### Description

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.

### Usage

    subsetSamples(object, samples)

### Arguments

`object` | a `MOFAmodel` object.
`samples` | character vector with the sample names, numeric vector with the sample indices or logical vector with the samples to be kept as TRUE.

### Value

`MOFAmodel` object with a subset of samples

### Examples

    # 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

[Package MOFA version 1.2.0 Index]