cachexiaData


A dataset containing the metabolite concentrations of 77 urine samples 
from cancer patients measured by 1H NMR


datasets

A collection of tools for multivariate analysis of metabolomics
data, which includes several preprocessing methods (normalization, scaling)
and various exploration and data visualization techniques (Principal
Components Analysis and Multi Dimensional Scaling). The core of the package
is the Random Forest algorithm used for the construction, optimization and
validation of classification models with the aim of identifying potentially
relevant biomarkers.

Piergiorgio Palla

RFmarkerDetector

Multivariate Analysis of Metabolomics Data using Random Forests

cachexiaData function

A data frame with 77 rows and 65 variables:

Format

Source

cachexiaData: Metabolite concentrations

Description

Usage

Arguments

Format

Source