Description Usage Arguments Details Author(s) References Examples

`centralPlot`

plots distinctly the [np] most central observations, where [np] is the largest integer smaller than np, and the remaining most external ones, according to the modified band depth.

1 2 |

`x` |
a data matrix containing the observations (samples) by rows and the variables (genes) by columns. |

`p` |
proportion of most central samples to be displayed. |

`col.c` |
the color for the central samples, either as a character string or as a number. Ignored if gradient is TRUE. |

`col.e` |
the color for the external samples. |

`lty` |
a vector of two components with the line type of the central and external curves. |

`gradient` |
a logical value. If TRUE then the most central curves are plotted with colors according to the gradient.ramp parameter. |

`gradient.ramp` |
an optional vector of two components containing the first and last colors of the palette used to color the most central curves. |

`main` |
a character string for the plot title. |

`cex` |
the magnification to be used for the legend. |

`...` |
further graphical parameters to be passed to 'plot'. |

The `centralPlot`

allows to visualise the most central curves within the dataset.

Sara Lopez-Pintado [email protected] and Aurora Torrente [email protected]

Lopez-Pintado, S. *et al.* (2010). Robust depth-based tools for the analysis of gene expression data. *Biostatistics*, 11 (2), 254-264.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
## simulated data
set.seed(0)
x <- matrix(rnorm(100),10,10)
centralPlot(x,p=0.2)
## real data
data(prostate)
prost.x<-prostate[,1:100]
prost.y<-prostate[,101]
centralPlot(prost.x[prost.y==0,], p=0.5) ## 50 % most central normal samples
centralPlot(prost.x[prost.y==1,], p=0.5, gradient=TRUE, main='Tumor samples')
## 50 % most central tumoral samples
``` |

depthTools documentation built on May 30, 2017, 1:34 a.m.

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