ZIQML.fit: Group and covariate effects on lncRNA counts by Generalized...

In lncDIFF: Long Non-Coding RNA Differential Expression Analysis

Description

ZIQML.fit estimates the group effect on gene expression using zero-inflated exponential quasi likelihood.

Usage

ZIQML.fit(edata, design.matrix, link = "log")

Arguments

edata	Normalized counts matrix with genes in rows and samples in columns.
design.matrix	Design matrix for groups and covariates, generated by model.matrix().
link	Link function for the generalized linear model and likelihood function,either 'log' or 'identity'. The default is 'log'.

Value

Estimates	Estimated group effect on gene expression by zero-inflated exponential quasi maximum likelihood (ZIQML) estimator.
logLikelihood	The value of zero-inflated quasi likelihood.
edata	lncRNA counts or expression matrix.
design.matrix	The design matrix of groups and covariates.
link	The specified link function.

Examples

data('hnsc.edata','design') 
# 'hnsc.edata' contains FPKM of 1000 lncRNA genes and 80 samples 
# 'design' is the design matrix for tissue and batch.

# For the first 100 genes  
# Fit GLM by ZIQML with logarithmic link function                                      
fit.log=ZIQML.fit(edata=hnsc.edata[1:100,],design.matrix=design,link='log') 

# Fit GLM by ZIQML with identity link function
fit.identity=ZIQML.fit(edata=hnsc.edata[1:100,],design.matrix=design,link='identity') 

lncDIFF documentation built on Jan. 17, 2020, 9:06 a.m.