PPsFUN: Posterior Probability Computation

In JingXieMIZZOU/BLMRM: A Bayesian Logistic Regression Model for Genome-Wide Detection of Allele-Specific Gene Expression

Description

A function to compute the posterior probabilities of 4 models which correspond to four different situations of gene expression, i.e., model 1 represents no ASE and no SNP variation; model 2 represents ASE without SNP variation; model 3 represents no ASE but significant SNP variation; model 4 represents ASE with significant SNP variation.

Usage

PPsFUN(par, index, data, rep)

Arguments

par	hyperparameters estimates returned by par.est function.
index	index of a specific gene, i.e., the gene number in raw data.
data	The raw data, need to be in the exact format with the sample data provided by this package, more specifically, a data.frame with its first 3 variables indicating gene ID, gene number and SNP number within a specific gene respectively. The following 2*Rep (Rep is the number of biological replicates) columns in the data.frame contain count data and the order must be consistent with the sample data. More details would be found in help(mysample).
rep	The number of biological replicates at each SNP.

Value

A 1x5 matrix contains the gene number of a specific gene and the logarithms of posterior probabilities of the 4 models for this gene.

JingXieMIZZOU/BLMRM documentation built on May 29, 2019, 7:31 a.m.