Combined_method: Combined_method: a R function for RNA-Seq data differential...
In DongmeiLi2017/ComSeq: ComSeq: An ensemble method for RNA-Seq differential analysis

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

This ensemble method combined four current methods (DESeq2, EBSeq, SAMSeq, NOISeq) with equal weight on their resulting FDR-adjusted P-values to identify significantly differentially expressed genes from RNA-Seq data.

1	Combined_method(RNAseqcount, label, alpha)

`RNAseqcount`	The input RNA-Seq count matrix with rows and columns denoting features and samples, respectively. The first column of the matrix denotes names of features.
`label`	A vector for group notation such as 1s denote treatment group and 0s denote control group
`alpha`	The signifiance level

The Combined method combined the analysis results from four current popular RNA-Seq differential analysis methods (DESeq2, EBSeq, SAMSeq, NOISeq) and declare a gene is significantly differentially expressed only when the gene is identified by all four methods.

Combined_method produces a named list with the following components:

`DESeq2.sig`	Feature names identified by DESeq2 differential analysis method
`EBSeq.sig`	Feature names identified by EBSeq differential analysis method
`SAMSeq.sig`	Feature names identified by SAMSeq differential analysis method
`NOISeq.sig`	Feature names identified by NOISeq differential analysis method
`Combined.sig`	Feature names identified by Combined differential analysis method
`Combined.sig.table`	Significant feature tables from combined method including original feature counts from all samples, test statistics from DESeq2 method, and adjusted P-values from DESeq2 method

Dongmei Li

Love MI, Huber W and Anders S (2014). “Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.” Genome Biology, 15, pp. 550. doi: 10.1186/s13059-014-0550-8. Leng N and Kendziorski C (2015). EBSeq: An R package for gene and isoform differential expression analysis of RNA-seq data. R package version 1.14.0. Tarazona S, Garcia-Alcalde F, Dopazo J, Ferrer A and Conesa A (2011). “Differential expression in RNA-seq: a matter of depth.” Genome Research, 21(12), pp. 4436.

The DESeq2, EBSeq, SAMSeq, and NOISeq packages.

system.file("data", package = "ComSeq")
data("Bottomly_count")
summary(Bottomly_count)
label <- c(rep(0, 10), rep(1, 11))
Result <- Combined_method(RNAseqcount = Bottomly_count, label = label, alpha = 0.05)
summary(Result)
Result