detection: ASE Detection

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

Description

A function to perform hypothesis tests.

Usage

detection(data, clean_index, paras, rep, fdr = 0.05)

Arguments

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).
clean_index	a vector contain index of genes without computational problems which would be returned by par.est function.
paras	hyperparameters estimates returned by par.est function.
rep	The number of biological replicates at each SNP.
fdr	The desired False Discovery Rate (FDR), default value was set as 0.05.

Value

A list contains the following:

geneEffect

A data.frame contains gene IDs and gene numbers of the genes with significant ASE and their corresponding posterior probabilities and estimated FDRs.

SNPEffect

A data.frame contains gene IDs and gene numbers of the genes with significant ASE variation across SNPs and their corresponding posterior probabilities and estimated FDRs.

GSEffect

A data.frame contains gene IDs and gene numbers of the genes exhibiting both ASE gene effect and ASE variation across SNPs and their corresponding posterior probabilities and estimated FDRs.

logPPs

a data.frame contains detailed intermediate results, i.e., the posterior probabilities of the 4 models for all the genes.

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