Combined_method: Combined_method: a R function for RNA-Seq data differential...

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

Description

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.

Usage

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Combined_method(RNAseqcount, label, alpha)

Arguments

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

Details

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.

Value

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

Author(s)

Dongmei Li

References

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.

See Also

The DESeq2, EBSeq, SAMSeq, and NOISeq packages.

Examples

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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

DongmeiLi2017/ComSeq documentation built on May 23, 2019, 10:31 p.m.