calculate_variance_explained_per_sample: Calculate variance explained by the MOFA factors for each...

In bioFAM/MOFA2: Multi-Omics Factor Analysis v2

Calculate variance explained by the MOFA factors for each sample

Description

This function takes a trained MOFA model as input and calculates, **for each sample** the proportion of variance explained (i.e. the coefficient of determinations (R^2)) by the MOFA factors across the different views.

Usage

calculate_variance_explained_per_sample(
  object,
  views = "all",
  groups = "all",
  factors = "all"
)

Arguments

object	a MOFA object.
views	character vector with the view names, or numeric vector with view indexes. Default is 'all'
groups	character vector with the group names, or numeric vector with group indexes. Default is 'all'
factors	character vector with the factor names, or numeric vector with the factor indexes. Default is 'all'

Value

a list with matrices with the amount of variation explained per sample and view.

Examples

# Using an existing trained model on simulated data
file <- system.file("extdata", "model.hdf5", package = "MOFA2")
model <- load_model(file)

# Calculate variance explained (R2)
r2 <- calculate_variance_explained_per_sample(model)

bioFAM/MOFA2 documentation built on Feb. 1, 2024, 6:41 a.m.