feature_weights-methods: Retrieve the matrix of feature weights from a SIAMCAT object

In zellerlab/siamcat: Statistical Inference of Associations between Microbial Communities And host phenoTypes

Retrieve the matrix of feature weights from a SIAMCAT object

Description

Function to extract the feature weights from a SIAMCAT object

Usage

feature_weights(siamcat, verbose=1)

## S4 method for signature 'siamcat'
feature_weights(siamcat, verbose = 1)

Arguments

siamcat	(Required). A siamcat-class object that contains trained models
verbose	integer, if the slot is empty, should a message be printed? values can be either 0 (no output) or 1 (print message)

Details

The function extracts the weight matrix from all trained models (see weight_matrix) and computes several metrics on the feature weights:

• mean.weight - mean weight across trained models

• median.weight - median weight across trained models

• sd.weight - standard deviation of the weight across trained models

• mean.rel.weight - mean relative weight across trained models (each model is normalized by the absolute of all weights)

• median.rel.weight - median relative weight across trained models

• sd.rel.weight - standard deviation of the relative weight across trained models

• percentage - percentage of models in which this feature was selected (i.e. non-zero)

Value

A dataframe containing mean/median feature weight and additional info or NULL

Examples

data(siamcat_example)
temp <- feature_weights(siamcat_example)
head(temp)

zellerlab/siamcat documentation built on Feb. 1, 2024, 2:21 a.m.