visualizeComponents
illustrates the factorization inferred by GFA,
averaging over the posteriors of the parameters, if they have been stored.
visualizeComponents(
model,
Y = NULL,
norm = NULL,
mode = 1,
showAll = TRUE,
hclust = FALSE,
topK = 3,
topFeatures = NA,
topSamples = NA
)
A list containing the matrices that have been visualized.
The learned GFA model.
The used input data to be plotted, if supplied. Default NULL.
The normalization acquired from normalizeData
, if
applied. If provided, the reconstruction is shown in the original data
space. Default NULL.
Determines which mode to visualize in case of pairing in two modes (default: 1).
Show the full predictions and factorizations? May be cumbersome for large data. Default TRUE.
Order features and samples based on hierarchical clustering? Default FALSE.
Number of strongest components visualized in the data space. Default 3.
How many most relevant features to show for the data space visualizations? Default NA, showing all the features.
How many most relevant samples to show for the data space visualizations? Default NA, showing all the samples.