plotTopWeights: Plot top weights

Description Usage Arguments Details Value Examples

View source: R/plotWeights.R

Description

Plot top weights for a given latent factor in a given view.

Usage

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plotTopWeights(object, view, factor, nfeatures = 10, abs = TRUE,
  scale = TRUE, sign = "both")

Arguments

object

a trained MOFAmodel object.

view

character vector with the view name, or numeric vector with the index of the view to use.

factor

character vector with the factor name, or numeric vector with the index of the factor to use.

nfeatures

number of top features to display. Default is 10.

abs

logical indicating whether to use the absolute value of the weights. Default is TRUE.

scale

logical indicating whether to scale all loadings from 0 to 1. Default is TRUE.

sign

can be 'positive', 'negative' or 'both' to show only positive, negative or all weigths, respectively. Default is 'both'.

Details

The weights, or the loadings, provide the mapping between the high-dimensional space (the genes) and the low-dimensional space (the factors).
They define a score for each gene on each factor, such that genes with no association with the factor are expected to have values close to zero, whereas genes with strong association with the factor are expected to have large absolute values.
The sign of the loading indicates the direction of the effect: A positive loading indicates that the feature is more active in the cells with positive factor values, while a negative loading indicates that the feature is more active in the cells with negative factor values.

Value

Returns a ggplot2 object

Examples

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# Example on the CLL data
filepath <- system.file("extdata", "CLL_model.hdf5", package = "MOFAdata")
MOFA_CLL <- loadModel(filepath)
plotTopWeights(MOFA_CLL, view="Mutations", factor=1, nfeatures=3)
plotTopWeights(MOFA_CLL, view="Mutations", factor=1, nfeatures=3, sign = "positive")
plotTopWeights(MOFA_CLL, view="Mutations", factor=1, nfeatures=3, sign = "negative")

# Example on the scMT data
filepath <- system.file("extdata", "scMT_model.hdf5", package = "MOFAdata")
MOFA_scMT <- loadModel(filepath)
plotTopWeights(MOFA_scMT, view="RNA expression", factor=1)

bioFAM/MOFA documentation built on Oct. 3, 2020, 12:53 a.m.