Visualization Options in methyldeconv

Visualization Options in methyldeconv

methyldeconv provides several functions to visualize the results of cell-type deconvolution analyses. This vignette demonstrates how to use these visualization tools with example data.

Example Data

We’ll use example data from the minfi and minfiData packages:

library(methyldeconv)
library(minfi)
library(minfiData)

# Example data
methyl_set <- minfiData::MsetEx
ratio_set <- minfi::ratioConvert(methyl_set)
beta_matrix <- minfi::getBeta(ratio_set)

# Run deconvolution
result <- methyldeconv::deconvolute(methyl_set = methyl_set, method = 'epidish')
result_multiple <- methyldeconv::deconvolute_combined(methyl_set = methyl_set,
                                                      methods = c('epidish','methylcc'),
                                                      array = '450k')

Barplot of Deconvolution Results

The results_barplot() function creates a barplot for each sample, showing the estimated cell-type fractions:

methyldeconv::results_barplot(result)

Boxplot of Deconvolution Results

The results_boxplot() function creates a boxplot for each cell type, summarizing the distribution of estimated fractions across samples:

methyldeconv::results_boxplot(result)

Aggregated Boxplot for Multiple Methods

If you run multiple methods using deconvolute_combined(), you can visualize the aggregated results with results_aggregated_boxplot():

methyldeconv::results_aggregated_boxplot(result_multiple)

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These visualization functions help you interpret and compare the results of different deconvolution methods. For more customization options, see the function documentation or explore the source code in the R/visualization.R file.