Description Usage Arguments Details Value Slots Methods Author(s) See Also Examples

Represents the posterior distribution used to infer copy number from targeted deep sequencing of multiple genes.

1 2 3 4 5 | ```
multiCNVPosterior(obs, prior)
## S4 method for signature 'MultiCNVPosterior'
summary(object, ...)
## S4 method for signature 'MultiCNVPosterior,missing'
plot(x, place="topright", lwd=1, ...)
``` |

`obs` |
List or data frame of observed read-count data |

`prior` |
Prior distribution, represented using the class |

`object` |
object of class |

`x` |
object of class |

`place` |
Character string; where to place the figure legend |

`lwd` |
Line width parameter. |

`...` |
extra arguments for generic or plotting routines |

The `DeepCNV`

class is used to fit a Bayesian model to targeted
sequencing data from one or a few genes in order to draw inferences
about possible copy number changes. Details on the algorithm can be
found in `CNVPrior`

and `CNVPosterior`

and in the
vignettes.

The `multiCNVPosterior`

function is the constructor for the
`MultiCNVPosterior`

class, and it implements the Bayesian
algorithm on targeted sequencing data from multiple genes. The key
point is that estimates of the posterior distribution on the fraction
*ν* of normal cells will be much more reliable by combining the
observed variants from several genes. In turn, this improved posterior
can yield better copy number calls for the genes.

Limitations: In the current implementation, the same discrete prior
distribution on the colpy number state must be used for all genes.
However, when multiple genes are sequenced, one should in principle be
able to use the read depth of different genes to get a better idea of
which ones are likely to be gained or lost, thus customizing the
priors (or better yet, formally adding this information to the
model). A second shortcoming is that there is currently no easy
way to convert the joint posterior distribution on the normal fraction
into an object of the class `CNVPrior`

to reuse it.

The `makemultiCNVPosterior`

constructor returns a valid object of the
class.

`gposts`

:List of

`CNVPosterior`

objects, one for each gene`cps`

An object of the

`CNVPosteriorSummary`

class.

- summary(object, ...)
Writes out a summary of the object

- plot(x, ...)
Plots the posteriro distribution on the normal fraction

Kevin R. Coombes krc@silicovore.com

`CNVPrior`

, `CNVPosterior`

, `cnvLikelihood`

1 2 3 4 5 6 7 8 9 | ```
prior <- setCNVPrior(alpha=1.2, beta=4.8, pAbnormal=0.6)
obs1 <- simReads(1, 9, 0.23, "Normal")
obs2 <- simReads(1, 7, 0.23, "Deleted")
observed <- list(G1 = obs1, G2=obs2)
rm(obs1, obs2)
prior <- setCNVPrior(alpha=1.2, beta=4.8, pAbnormal=0.6)
mpost <- multiCNVPosterior(observed, prior)
summary(mpost)
plot(mpost, main="Posterior Distribution on Nomral Fraction")
``` |

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