# The Nutrimouse Dataset

### Description

The data come from a study of the effects of five dietary regimens with different fatty acid compositions on liver lipids and hepatic gene expression in 40 mice.

### Usage

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### Format

A data frame with 40 observations on the following 143 variables.

`genotype`

a factor with levels

`wt`

`ppar`

`diet`

a factor with levels

`coc`

`fish`

`lin`

`ref`

`sun`

`X36b4`

a numeric vector

`ACAT1`

a numeric vector

`ACAT2`

a numeric vector

`ACBP`

a numeric vector

`ACC1`

a numeric vector

`ACC2`

a numeric vector

`ACOTH`

a numeric vector

`ADISP`

a numeric vector

`ADSS1`

a numeric vector

`ALDH3`

a numeric vector

`AM2R`

a numeric vector

`AOX`

a numeric vector

`BACT`

a numeric vector

`BIEN`

a numeric vector

`BSEP`

a numeric vector

`Bcl.3`

a numeric vector

`C16SR`

a numeric vector

`CACP`

a numeric vector

`CAR1`

a numeric vector

`CBS`

a numeric vector

`CIDEA`

a numeric vector

`COX1`

a numeric vector

`COX2`

a numeric vector

`CPT2`

a numeric vector

`CYP24`

a numeric vector

`CYP26`

a numeric vector

`CYP27a1`

a numeric vector

`CYP27b1`

a numeric vector

`CYP2b10`

a numeric vector

`CYP2b13`

a numeric vector

`CYP2c29`

a numeric vector

`CYP3A11`

a numeric vector

`CYP4A10`

a numeric vector

`CYP4A14`

a numeric vector

`CYP7a`

a numeric vector

`CYP8b1`

a numeric vector

`FAS`

a numeric vector

`FAT`

a numeric vector

`FDFT`

a numeric vector

`FXR`

a numeric vector

`G6PDH`

a numeric vector

`G6Pase`

a numeric vector

`GK`

a numeric vector

`GS`

a numeric vector

`GSTa`

a numeric vector

`GSTmu`

a numeric vector

`GSTpi2`

a numeric vector

`HMGCoAred`

a numeric vector

`HPNCL`

a numeric vector

`IL.2`

a numeric vector

`L.FABP`

a numeric vector

`LCE`

a numeric vector

`LDLr`

a numeric vector

`LPK`

a numeric vector

`LPL`

a numeric vector

`LXRa`

a numeric vector

`LXRb`

a numeric vector

`Lpin`

a numeric vector

`Lpin1`

a numeric vector

`Lpin2`

a numeric vector

`Lpin3`

a numeric vector

`M.CPT1`

a numeric vector

`MCAD`

a numeric vector

`MDR1`

a numeric vector

`MDR2`

a numeric vector

`MRP6`

a numeric vector

`MS`

a numeric vector

`MTHFR`

a numeric vector

`NGFiB`

a numeric vector

`NURR1`

a numeric vector

`Ntcp`

a numeric vector

`OCTN2`

a numeric vector

`PAL`

a numeric vector

`PDK4`

a numeric vector

`PECI`

a numeric vector

`PLTP`

a numeric vector

`PMDCI`

a numeric vector

`PON`

a numeric vector

`PPARa`

a numeric vector

`PPARd`

a numeric vector

`PPARg`

a numeric vector

`PXR`

a numeric vector

`Pex11a`

a numeric vector

`RARa`

a numeric vector

`RARb2`

a numeric vector

`RXRa`

a numeric vector

`RXRb2`

a numeric vector

`RXRg1`

a numeric vector

`S14`

a numeric vector

`SHP1`

a numeric vector

`SIAT4c`

a numeric vector

`SPI1.1`

a numeric vector

`SR.BI`

a numeric vector

`THB`

a numeric vector

`THIOL`

a numeric vector

`TRa`

a numeric vector

`TRb`

a numeric vector

`Tpalpha`

a numeric vector

`Tpbeta`

a numeric vector

`UCP2`

a numeric vector

`UCP3`

a numeric vector

`VDR`

a numeric vector

`VLDLr`

a numeric vector

`Waf1`

a numeric vector

`ap2`

a numeric vector

`apoA.I`

a numeric vector

`apoB`

a numeric vector

`apoC3`

a numeric vector

`apoE`

a numeric vector

`c.fos`

a numeric vector

`cHMGCoAS`

a numeric vector

`cMOAT`

a numeric vector

`eif2g`

a numeric vector

`hABC1`

a numeric vector

`i.BABP`

a numeric vector

`i.BAT`

a numeric vector

`i.FABP`

a numeric vector

`i.NOS`

a numeric vector

`mABC1`

a numeric vector

`mHMGCoAS`

a numeric vector

`C14.0`

a numeric vector

`C16.0`

a numeric vector

`C18.0`

a numeric vector

`C16.1n.9`

a numeric vector

`C16.1n.7`

a numeric vector

`C18.1n.9`

a numeric vector

`C18.1n.7`

a numeric vector

`C20.1n.9`

a numeric vector

`C20.3n.9`

a numeric vector

`C18.2n.6`

a numeric vector

`C18.3n.6`

a numeric vector

`C20.2n.6`

a numeric vector

`C20.3n.6`

a numeric vector

`C20.4n.6`

a numeric vector

`C22.4n.6`

a numeric vector

`C22.5n.6`

a numeric vector

`C18.3n.3`

a numeric vector

`C20.3n.3`

a numeric vector

`C20.5n.3`

a numeric vector

`C22.5n.3`

a numeric vector

`C22.6n.3`

a numeric vector

### Details

The data come from a study of the effects of five dietary regimens with different fatty acid compositions on liver lipids and hepatic gene expression in wild-type and PPAR-alpha-deficient mice (Martin et al., 2007).

There were 5 replicates per genotype and diet combination.

There are two design variables: (i) genotype, a factor with two levels: wild-type (wt) and PPAR-alpha-deficient (ppar), and (ii) diet, a factor with five levels. The oils used for experimental diet preparation were: corn and colza oils (50/50) for a reference diet (ref); hydrogenated coconut oil for a saturated fatty acid diet (coc); sunflower oil for an Omega6 fatty acid-rich diet (sun); linseed oil for an Omega3-rich diet (lin); and corn/colza/enriched (43/43/14) fish oils (fish).

There are 141 response variables: (i) the log-expression levels of 120 genes measured in liver cells, and (ii) the concentrations (in percentages) of 21 hepatic fatty acids measured by gas chromatography.

### Source

The data were provided by Pascal Martin from the Toxicology and Pharmacology Laboratory, National Institute for Agronomic Research, French.

### References

Martin, P. G. P., Guillou, H., Lasserre, F., D<e9>jean, S., Lan, A., Pascussi, J.-M., San Cristobal, M., Legrand, P., Besse, P. and Pineau, T. (2007). Novel aspects of PPARa-mediated regulation of lipid and xenobiotic metabolism revealed through a multrigenomic study. Hepatology 54, 767-777.

### Examples

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