GSReg_SEVA: Applies Splice-EVA (SEVA) algorithm

Description Usage Arguments Value Author(s) See Also Examples

Description

GSReg.SEVA identifies Differential Spliced genes by assigning p-value by SEVA.

Usage

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 function(juncExprs,
		  phenoVect, 
          verbose=T,
          sparse =F, ...)

Arguments

juncExprs

A matrix containing junction expression whose columns represent samples. Rows correspond to junctions and whose names are formed in the following format, chrN:D-A, N represents chromosome number, D represents the start coordination coordinate and A the acceptor end coordinationcoordinate. If geneexprs is not specified, SEVA statistics are independent of the coordinates for junction expression because they are rank-based . Otherwise, junction expression would be log transformed and apply the same quantification method as used for total gene expression in geneexprs for optimal filtering.

phenoVect

a factor containing the labels for columns of juncExprs.

verbose

If True, reports that if the progress of the analysis after every 100 genes are analyzed.

sparse

Use sparse matrices for junctions overlap. Not recommended unless you run out of memory.

...

Parameters would be passed to GSReg.OverlapJunction function.

Value

a list of analysis for all genes.

$E1

the modified variance on the pathway within the samples from levels(phenotypes)[1].

$E2

the modified variance on the pathway within the samples from levels(phenotypes)[2].

$E12

the modified variance on the pathway across the samples from levels(phenotypes)[1] tolevels(phenotypes)[2].

$VarEta1

the estimation of the modified variance on the pathway within the samples from levels(phenotypes)[1].

$VarEta2

the estimation of the modified variance on the pathway within the samples from levels(phenotypes)[2].

$zscore

zscore for the modified variance.

$zscoreD12D1

zscoreD12D1 for the modified variance.

$zscoreD12D2

zscoreD12D2 for the modified variance.

$pvalue

theoretical p-value for null E1 = E2. (Standard EVA).

$pvalueD12D1

theoretical p-value for null E1 = E12.

$pvalueD12D2

theoretical p-value for null E2 = E12.

$pvalueTotal

Bonferonni corrected p-value of the three p-values.

Author(s)

Bahman Afsari

See Also

GSReg.OverlapJunction,GSReg.GeneSets.DIRAC,GSReg.GeneSets.EVA

Examples

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library(GSReg)
require('Homo.sapiens')
require('org.Hs.eg.db')
require('GenomicRanges')



data(juncExprsSimulated)
SEVAjunc <- GSReg.SEVA(juncExprs = junc.RPM.Simulated,
                       phenoVect = phenotypes,
                       geneexpr = geneExrsGSReg)
                       
print(sapply(SEVAjunc,function(x) x$pvalue))

afsari/GSReg documentation built on May 9, 2019, 3:39 p.m.