Description Usage Arguments Details Value Author(s) References Examples

This function calculates the biplot method through the compromise matrix to select genes SelectVar from DiStatis Class Object High level constructor of SelectVar class object

1 2 3 4 5 6 |

`object` |
Object is an object of DiStatis Class. |

`ord` |
Logical. If TRUE, the models with intercept are computed, else the intercept is zero. |

`Crit` |
c("R2-Adj","p-val(Bonf)","AIC","BIC").Criterious of selection. "R2-Adj","p-val (Bonf)","AIC","BIC". Choose "R2-Adj" or "p-val (Bonf)" (Bonferroni correction),"AIC" or "BIC". |

`perc` |
The value of percentil that indicate how much data than are selected. |

`Dims` |
Numeric that indicates the number of dimensions to use for do the model. Default is 2. |

This function allows to build the biplot for continuous response, using an external procedure to obtained the regresors in the linear model (the response being an continuous variable). This function allows the selection of genes using the goodness of fit of the Models Biplot. object,ord=FALSE,

`SelectVar` |
SelectVar class object with the corresponding completed slots according to the given model |

M L Zingaretti, J A Demey-Zambrano, J L Vicente Villardon, J R Demey

Demey, J., Vicente-Villardon, J. L., Galindo, M.P. & Zambrano, A. (2008) Identifying Molecular Markers Associated With Classification Of Genotypes Using External Logistic Biplots. Bioinformatics, 24(24), 2832-2838.

Gabriel, K. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika 58(3), 453–467.

Gower, J. & Hand, D. (1996). Biplots, Monographs on statistics and applied probability. 54. London: Chapman and Hall., 277 pp.

1 2 3 4 5 6 | ```
{
data(NCI60Selec)
Z1<-DiStatis(NCI60Selec)
M1<-SelectVar(Z1,Crit="R2-Adj",perc=0.95)
M2<-SelectVar(Z1,Crit="p-val(Bonf)",perc=0.95)
}
``` |

kimod documentation built on Nov. 1, 2018, 3:16 a.m.

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