lncDIFF: lncRNA Differential Expression (DE) analysis

In lncDIFF: Long Non-Coding RNA Differential Expression Analysis

Description

lncDIFF returns DE analysis results based on lncRNA counts and grouping variables.

Usage

lncDIFF(
  edata,
  group,
  covariate = NULL,
  link.function = "log",
  CompareGroups = NULL,
  simulated.pvalue = FALSE,
  permutation = 100
)

Arguments

edata	Normalized counts matrix with genes in rows and samples in columns.
group	Primary factor of interest in DE analysis, e.g., treatment groups, tissue types, other phenotypes.
covariate	Other variables (or covariates) associated with expression level. Input must be a matrix or data frame with each column being a covariate matching to group
link.function	Link function for the generalized linear model, either 'log' or 'identity', default as 'log'.
CompareGroups	Labels of treatment groups or phenotypes of interest to be compared in DE analysis. Input must be a vector of group labels without duplicates.
simulated.pvalue	If empirical p-values are computed, simulated.pvalue=TRUE. The default is FALSE.
permutation	The number of permutations used in simulating pvalues. The default value is 100.

Value

DE.results	Likelihood ratio test results with test statistics, p-value, FDR, DE genes, groupwise mean expression, fold change (if two groups are compared). If simulated.pvalue=TRUE, test.results also includes simulated p-value and FDR.
full.model.fit	Generalized linear model with zero-inflated Exponential likelihood function, estimating group effect compared to a reference group.

References

Li, Q., Yu, X., Chaudhary, R. et al.'lncDIFF: a novel quasi-likelihood method for differential expression analysis of non-coding RNA'. BMC Genomics (2019) 20: 539.

Examples

data('hnsc.edata','tissue','cov')  

# DE analysis comparing two groups (normal vs tumor) for 100 genes
result=lncDIFF(edata=hnsc.edata[1:100,],group=tissue,covariate=cov) 

# Recommend at least 50 permutations if simulated.pvalue=TRUE

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