jointPosterior: jointPosterior

In scDD: Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions

Description

Function to obtain the normalized joint posterior of the data and partition.

Usage

jointPosterior(y, mcobj, alpha, m0, s0, a0, b0)

Arguments

y	Numeric data vector for one gene (log-transformed non-zeroes)
mcobj	Object returned by mclustRestricted
alpha	Value for the Dirichlet concentration parameter
m0	Prior mean value for generating distribution of cluster means
s0	Prior precision value for generating distribution of cluster means
a0	Prior shape parameter value for the generating distribution of cluster precision
b0	Prior scale parameter value for the generating distribution of cluster precision

Details

Calculates the normalized joint posterior of the data and partition under the Product Partition Model formulation of the Dirichlet Process Mixture model.

Value

log joint posterior value

References

Korthauer KD, Chu LF, Newton MA, Li Y, Thomson J, Stewart R, Kendziorski C. A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Genome Biology. 2016 Oct 25;17(1):222. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1077-y

scDD documentation built on Nov. 8, 2020, 7:10 p.m.