View source: R/model_interpretation_plot.R
model.interpretation.plot | R Documentation |
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)
siamcat |
object of class siamcat-class |
fn.plot |
string, filename for the pdf-plot |
color.scheme |
color scheme for the heatmap, defaults to |
consens.thres |
float, minimal ratio of models incorporating a feature
in order to include it into the heatmap, defaults to |
heatmap.type |
string, type of the heatmap, can be either |
limits |
vector, cutoff for extreme values in the heatmap,
defaults to |
log.n0 |
float, pseudocount to be added before log-transformation
of features, defaults to |
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: |
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.
Does not return anything, but produces the model interpretation plot.
data(siamcat_example)
# simple working example
siamcat_example <- train.model(siamcat_example, method='lasso')
model.interpretation.plot(siamcat_example, fn.plot='./interpretion.pdf',
heatmap.type='zscore')
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.