R: Liver Toxicity Data

liver.toxicity {mixOmics} | R Documentation

## Liver Toxicity Data

### Description

This data set contains the expression measure of 3116 genes and 10 clinical measurements for 64 subjects (rats) that were exposed to non-toxic, moderately toxic or severely toxic doses of acetaminophen in a controlled experiment.

### Usage

    data(liver.toxicity)

### Format

A list containing the following components:

`gene`

  data frame with 64 rows and 3116 columns. The expression measure of 3116 genes for the 64 subjects (rats).

`clinic`

  data frame with 64 rows and 10 columns, containing 10 clinical variables for the same 64 subjects.

`treatment`

  data frame with 64 rows and 4 columns, containing the treatment information on the 64 subjects, such as doses of acetaminophen and times of necropsies.

`gene.ID`

  data frame with 3116 rows and 2 columns, containing geneBank IDs and gene titles of the annotated genes

### Details

The data come from a liver toxicity study (Bushel et al., 2007) in which 64 male rats of the inbred strain Fisher 344 were exposed to non-toxic (50 or 150 mg/kg), moderately toxic (1500 mg/kg) or severely toxic (2000 mg/kg) doses of acetaminophen (paracetamol) in a controlled experiment. Necropsies were performed at 6, 18, 24 and 48 hours after exposure and the mRNA from the liver was extracted. Ten clinical chemistry measurements of variables containing markers for liver injury are available for each subject and the serum enzymes levels are measured numerically. The data were further normalized and pre-processed by Bushel et al. (2007).

### Source

The two liver toxicity data sets are a companion resource for the paper of Bushel et al. (2007), and was downloaded from:

http://www.biomedcentral.com/1752-0509/1/15/additional/

### References

Bushel, P., Wolfinger, R. D. and Gibson, G. (2007). Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes. BMC Systems Biology 1, Number 15.

Lê Cao, K.-A., Rossouw, D., Robert-Granie, C. and Besse, P. (2008). A sparse PLS for variable selection when integrating Omics data. Statistical Applications in Genetics and Molecular Biology 7, article 35.

[Package mixOmics version 6.3.2 Index]