View source: R/optCluster-Functions.R

aggregPlot | R Documentation |

`aggregPlot`

displays a figure representing the results from rank
aggregation.

aggregPlot(x, show.average = TRUE, show.legend = TRUE, colR = "red", ...)

`x` |
An object of class |

`show.average` |
If |

`show.legend` |
If |

`colR` |
A character string specifying the line color for the optimal ranked list. |

`...` |
Additional plotting parameters. |

This function will produce a visual representation of rank aggregation results in three plots combined into a single figure. The top left plot displays the minimum values of the objective function as the number of iterations increases. The top right plot is a histogram of the objective function scores at the last iteration. The bottom plot shows the individual ranks of the clustering algorithms from the data (in grey), the final "optimal" rankings (in red), and the average ranking of each clustering algorithm (in black).

Pihur, V., Datta, S. and Datta, S. (2009). RankAggreg, an R package for weighted rank aggregation. BMC Bioinformatics, 10:62, https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-62.

`RankAggreg`

, `optCluster-class`

## This example may take a few minutes to compute ## Obtain Dataset data(arabid) ## Normalize Data with Respect to Library Size obj <- t(t(arabid)/colSums(arabid)) ## Analysis of Normalized Data using Internal and Stability Validation Measures norm1 <- optCluster(obj, 2:4, clMethods = "all") aggregPlot(norm1)

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