Model Interpretation Plot — model.interpretation.plot • SIAMCAT

This function produces a plot for model interpretation

model.interpretation.plot(siamcat, fn.plot = NULL,
color.scheme = "BrBG", consens.thres = 0.5, heatmap.type = "zscore",
limits = c(-3, 3), log.n0 = 1e-06, max.show = 50, prompt=TRUE,
verbose = 1)

Arguments

siamcat: object of class siamcat-class
fn.plot: string, filename for the pdf-plot
color.scheme: color scheme for the heatmap, defaults to 'BrBG'
consens.thres: float, minimal ratio of models incorporating a feature in order to include it into the heatmap, defaults to 0.5 Note that for 'randomForest' models, this cutoff specifies the minimum median Gini coefficient for a feature to be included and should therefore be much lower, e.g. 0.01
heatmap.type: string, type of the heatmap, can be either 'fc' or 'zscore', defaults to 'zscore'
limits: vector, cutoff for extreme values in the heatmap, defaults to c(-3, 3)
log.n0: float, pseudocount to be added before log-transformation of features, defaults to 1e-06
max.show: integer, maximum number of features to be shown in the model interpretation plot, defaults to 50
prompt: boolean, turn on/off prompting user input when not plotting into a pdf-file, defaults to TRUE
verbose: control output: 0 for no output at all, 1 for only information about progress and success, 2 for normal level of information and 3 for full debug information, defaults to 1

Value

Does not return anything, but produces the model interpretation plot.

Details

Produces a plot consisting of

a barplot showing the feature weights and their robustness (i.e. in what proportion of models have they been incorporated)
a heatmap showing the z-scores of the metagenomic features across samples
another heatmap displaying the metadata categories (if applicable)
a boxplot displaying the poportion of weight per model that is actually shown for the features that are incorporated into more than consens.thres percent of the models.

Examples

data(siamcat_example)

# simple working example
siamcat_example <- train.model(siamcat_example, method='lasso')
#> Trained lasso models successfully.
model.interpretation.plot(siamcat_example, fn.plot='./interpretion.pdf',
    heatmap.type='zscore')
#> Successfully plotted model interpretation plot to: ./interpretion.pdf