Express function to carry out XBSeq analysis

Description

A wrapper function to carry out XBSeq analysis procedure

Usage

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XBSeq(counts, bgcounts, conditions, method = "pooled", 
   sharingMode = "maximum", fitType = "local", pvals_only = FALSE, paraMethod='NP', big_count = 900)

Arguments

counts

A data.frame or matrix contains the observed signal

bgcounts

A data.frame or matrix contains the background noise

conditions

A factor to specify the experimental design

method

Method used to estimate SCV

sharingMode

Mode of sharing of information

fitType

Option to fit mean-SCV relation

pvals_only

Logical; Specify whether to extract pvalues only

paraMethod

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

Details

This is the express function for carry out differential expression analysis. Two methods can be choosen from for paraMethod. 'NP' stands for non-parametric method. 'MLE' stands for maximum liklihood estimation method. 'NP' is generally recommended for experiments with replicates smaller than 5.

Value

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

Author(s)

Yuanhang Liu

References

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.

See Also

estimateRealCount, XBSeqDataSet, estimateSCV, XBSeqTest

Examples

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   conditions <- c(rep('C1', 3), rep('C2', 3))
   data(ExampleData)
   Stats <- XBSeq(Observed, Background, conditions)