IVAS (version 1.4.0)

calSignificant: Calculates P.values by using two statistical models.

Description

calculates P.values for association between expressions and genotypes by using the linear regression model and/or generalized linear mixed model.

Usage

calSignificant(tx.gene=NULL, total.locus=NULL, exon.locus=NULL, intron.locus=NULL, 
info.strand=NULL, overapvalue=NULL, chrnum=NULL, expdata=NULL, snpdata=NULL, method=NULL)

Arguments

tx.gene

The matrix of transcripts including transcript IDs, Ensembl gene names, Ensembl transcript names, transcript start sites, and transcript end sites.

total.locus

Ranges including alternative exons and flanking introns in a gene.

exon.locus

All exon locus of a single gene.

intron.locus

All intron locus of a single gene.

info.strand

The strand informatrion of a single gene (forward strand = "+", reverse strand = "-").

overapvalue

Snps located in the alternative exons and the flanking introns

chrnum

The chromosome number of a single gene.

expdata

Dataframe of expression data.

snpdata

Datafame of genotype data.

method

The option for statistical models and boxplot.("lm" : analysis using linear regression model, "glm" : analysis using generalized linear mixed model, "both" : "lm" and "glm", and "boxplot" : for writing boxplot).

Value

The lm or glm method returns matrix including; SNP marker IDs, Chromosome numbers, alternative exons ranges, Intron rangess, alternative types, P values, information of differential median values of expression ratio among genotypes ("sig" if differential median > 0.1 and "not sig" otherwise), gene names, and methods ("lm" or "glm"). The boxplot method returns matrix with relative ratio values and genotypes of samples.

References

Chambers, J. M. (1992) Linear models. Chapter 4 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole. Breslow, N.E. Clayton, D.G. (1993). Approximate Inference in Generalized Linear Mixed Models. Journal of the American Statistical Association 88.

See Also

findOverlaps, lm, glmer