XBSeqTest: XBSeq test for differential expression
In XBSeq: Test for differential expression for RNA-seq data

Description Usage Arguments Details Value Author(s) References See Also Examples

The same method is adopted from DESeq for testing differential expression

1	XBSeqTest(XB, condA, condB, pvals_only = FALSE, method = c("NP", "MLE"), big_count = 900)

`XB`	A XBSeqDataSet object
`condA`	Factor level specified for condition A
`condB`	Factor level specified for condition B
`pvals_only`	Logical;whether or not only extract p values
`method`	method to use for estimation of distribution parameters, 'NP' or 'MLE'. See details section for details
`big_count`	An integer specify a count number above which where be considerred as 'big' and beta approximation will be used instead for testing differential expression

Differential expression analysis based on statistical methods proposed for DESeq. Details about the method can be found in DESeq manual page. Two methods can be choosen from for method. 'NP' stands for non-parametric method. 'MLE' stands for maximum liklihood estimation method. 'NP' is generally recommended for experiments with replicates smaller than 5.

A data.frame with following columns:

`id`	rownames of XBSeqDataSet
`baseMean`	The basemean for all genes
`baseMeanA`	The basemean for condition 'A'
`baseMeanB`	The basemean for condition 'B'
`foldChange`	The fold change compare condition 'B' to 'A'
`log2FoldChange`	The log2 fold change
`pval`	The p value for all genes
`padj`	The adjusted p value for all genes

Yuanhang Liu

H. I. Chen, Y. Liu, Y. Zou, Z. Lai, D. Sarkar, Y. Huang, et al., "Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads," BMC Genomics, vol. 16 Suppl 7, p. S14, Jun 11 2015.

XBSeq, estimateSCV

   data(ExampleData)
   conditions <- factor(c(rep('C1', 3), rep('C2', 3)))
   XB <- XBSeqDataSet(Observed, Background, conditions)
   XB <- estimateRealCount(XB)
   XB <- estimateSizeFactors(XB)
   XB <- estimateSCV(XB)
   Teststas <- XBSeqTest(XB, levels(conditions)[1L], levels(conditions)[2L])
   str(Teststas)