Description Usage Arguments Author(s) Examples

Makes formatted density plots from the posterior data frame(s) returned by CNVtest.binary

1 |

`posterior` |
The posterior distribution obtained from the CNVtools fitting algorithm, for example using CNVtest.binary |

`hist.or.dens` |
Either 'histogram' or 'density' to plot the data as an histogram or using a kernel density estimator |

`batch` |
character vector (usually of length 1, but not always), designing the batches one wants to plot. |

`freq` |
This argument is only relevant when hist.or.dens='histogram' (the default). It matches the argument freq of the hist function. With freq = FALSE frequencies, and not raw counts, are shown in the histogram. |

`...` |
Usual arguments passed to the hist function, including main or breaks for example. |

Vincent Plagnol [email protected] and Chris Barnes [email protected]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
#Load data for CNV for two control cohorts
data(A112)
raw.signal <- as.matrix(A112[, -c(1,2)])
dimnames(raw.signal)[[1]] <- A112$subject
#Extract CNV signal using principal components
pca.signal <- apply.pca(raw.signal)
#Extract batch, sample and trait information
batches <- factor(A112$cohort)
sample <- factor(A112$subject)
trait <- ifelse( A112$cohort == '58C', 0, 1)
#Fit the CNV with a three component model
fit.pca <- CNVtest.binary(signal = pca.signal, sample = sample, batch = batches,
disease.status = trait, ncomp = 3, n.H0=3, n.H1=3,
model.disease = "~ cn")
cnv.plot(fit.pca[['posterior.H0']], batch = '58C', breaks = 30)
``` |

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