Last data update: 2014.03.03

R: Alzheimer's Disease CSF Data
AlzheimerDiseaseR Documentation

Alzheimer's Disease CSF Data

Description

Washington University conducted a clinical study to determine if biological measurements made from cerebrospinal fluid (CSF) can be used to diagnose or predict Alzheimer's disease (Craig-Schapiro et al. 2011). These data are a modified version of the values used for the publication.

The R factor vector diagnosis contains the outcome data for 333 of the subjects. The demographic and laboratory results are collected in the data frame predictors.

One important indicator of Alzheimer's disease is the genetic background of a subject. In particular, what versions of the Apolipoprotein E gene inherited from one's parents has an association with the disease. There are three variants of the gene: E2, E3 and E4. Since a child inherits a version of the gene from each parent, there are six possible combinations (e.g. E2/E2, E2/E3, and so on). This data is contained in the predictor column named Genotype.

Usage

data(AlzheimerDisease)

Value

diagnosis

labels for the patients, either "Impaired" or "Control".

predictors

predictors for demographic data (eg. age, gender), genotype and assay results.

Source

Craig-Schapiro, R., Kuhn, M., Xiong, C., Pickering, E. H., Liu, J., Misko, T. P., Perrin, R. J., et al. (2011). Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis. PLoS ONE, 6(4), e18850.

Examples

data(AlzheimerDisease)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(AppliedPredictiveModeling)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AppliedPredictiveModeling/AlzheimerDisease.Rd_%03d_medium.png", width=480, height=480)
> ### Name: AlzheimerDisease
> ### Title: Alzheimer's Disease CSF Data
> ### Aliases: diagnosis predictors
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(AlzheimerDisease)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>