Plot abundances by class

This function plots a heatmap of the "n" features with greatest variance across rows.

1 |

`obj` |
A MRexperiment object with count data. |

`n` |
The number of features to plot. This chooses the "n" features with greatest variance. |

`norm` |
Whether or not to normalize the counts - if MRexperiment object. |

`log` |
Whether or not to log2 transform the counts - if MRexperiment object. |

`fun` |
Function to calculate pair-wise relationships. Default is pearson correlation |

`...` |
Additional plot arguments. |

plotted correlation matrix

1 2 3 | ```
data(mouseData)
plotCorr(obj=mouseData,n=200,cexRow = 0.4,cexCol = 0.4,trace="none",dendrogram="none",
col = colorRampPalette(brewer.pal(9, "RdBu"))(50))
``` |

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