03-multiPosterior: Class "MultiCNVPosterior"

In DeepCNV: Exploiting Normal Contamination to Infer Copy Number from Deep Sequencing

Description

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

Usage

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

Arguments

obs	List or data frame of observed read-count data
prior	Prior distribution, represented using the class multiCNVPrior.
object	object of class multiCNVPosterior
x	object of class CNVPosterior
place	Character string; where to place the figure legend
lwd	Line width parameter.
...	extra arguments for generic or plotting routines

Details

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.

Value

The makemultiCNVPosterior constructor returns a valid object of the class.

Slots

gposts:

List of CNVPosterior objects, one for each gene

cps

An object of the CNVPosteriorSummary class.

Methods

summary(object, ...)

Writes out a summary of the object

plot(x, ...)

Plots the posteriro distribution on the normal fraction

Author(s)

Kevin R. Coombes [e-mail]

See Also

CNVPrior, CNVPosterior, cnvLikelihood

Examples

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")

DeepCNV documentation built on May 2, 2019, 5:23 p.m.