Description Usage Arguments Details Value Author(s) Examples

View source: R/histogramPlot.R

`histogramPlot`

plots histograms of correlation values in expression data and
its reference.

1 2 3 4 5 6 7 8 9 10 | ```
histogramPlot(
X,
Y,
legend,
breaks = 40,
title,
col.X = "red",
col.Y = "black",
line = NULL
)
``` |

`X` |
A matrix or a list of matrices of estimated gene-gene correlations. |

`Y` |
A matrix of reference gene-gene correlations (i.e. known underlying correlation structure). |

`legend` |
A vector of character strings describing the data contained in |

`breaks` |
one of: a vector giving the breakpoints between histogram cells, a function to compute the vector of breakpoints, a single number giving the number of cells for the histogram, a character string naming an algorithm to compute the number of cells (see ‘Details’), a function to compute the number of cells.
In the last three cases the number is a suggestion only; as the
breakpoints will be set to |

`title` |
A character string describing title. |

`col.X` |
A vector or character string defining the color/colors associated with the data contained in |

`col.Y` |
The color associated with the data in |

`line` |
A vector giving the line type. |

The default for breaks is `"Sturges"`

.
Other names for which algorithms are supplied are `"Scott"`

and `"FD"`

/ `"Freedman-Diaconis"`

Case is ignored and partial
matching is used. Alternatively, a function can be supplied which will compute the
intended number of breaks or the actual breakpoints as a function of `x`

.

`histogramPlot`

returns a plot.

Saskia Freytag

1 2 3 4 5 6 7 8 9 10 11 | ```
Y<-simulateGEdata(500, 500, 10, 2, 5, g=NULL, Sigma.eps=0.1,
250, 100, intercept=FALSE, check.input=FALSE)
Y.hat<-RUVNaiveRidge(Y, center=TRUE, nc_index=251:500, 0, 10, check.input=FALSE)
Y.hat.cor<-cor(Y.hat[,1:100])
try(dev.off(), silent=TRUE)
par(mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0, mfrow=c(1, 1))
histogramPlot(Y.hat.cor, Y$Sigma[1:100, 1:100], title="Simulated data",
legend=c("RUV", "Truth"))
try(dev.off(), silent=TRUE)
histogramPlot(list(Y.hat.cor, cor(Y$Y[, 1:100])), Y$Sigma[1:100, 1:100],
title="Simulated data", col.Y="black", legend=c("RUV", "Raw", "Truth"))
``` |

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