| GWASdata {kangar00} | R Documentation |
S4 class for an object representing a Genome-wide Assocaition Study.
Description
S4 class for an object representing a Genome-wide Assocaition Study.
'GWASdata' is a GWASdata object constructor.
show displays basic information on GWASdata object
summary summarizes the content of a GWASdata object
and gives an overview about the information included in a
GWASdata object. Summary statistics for phenotype and genotype
data are calculated.
GeneSNPsize creates a data.frame of pathway
names with numbers of snps and genes in each pathway.
Usage
GWASdata(object, ...)
## S4 method for signature 'ANY'
GWASdata(geno, anno, pheno = NULL, desc = "")
## S4 method for signature 'GWASdata'
show(object)
## S4 method for signature 'GWASdata'
summary(object)
## S4 method for signature 'GWASdata'
GeneSNPsize(object)
Arguments
object |
A |
... |
Further arguments can be added to the function. |
geno |
An object of any type, including the genotype information. |
anno |
A |
pheno |
A |
desc |
A |
Methods (by generic)
-
GeneSNPsize(GWASdata): creates adata.frameofpathwaynames with numbers of snps and genes in each pathway.
Slots
genoAn object of any type, including genotype information. The format needs to be one line per individual and on colum per SNP in minor-allele coding (0,1,2). Other values between 0 and 2, as from impute dosages, are allowed. Missing values must be imputed prior to creation of a
GWASdataobject.annoA
data.framemapping SNPs to genes and genes to pathways. Needs to include the columns 'pathway' (pathway ID, e.g. hsa number from KEGG database), 'gene' (gene name (hgnc_symbol)), 'chr' (chromosome), 'snp' (rsnumber) and 'position' (base pair position of SNP).phenoA
data.framespecifying individual IDs, phenotypes and covariates to be included in the regression model e.g. ID, pheno, sex, pack.years. Note: IDs have to be in the first column!descA
charactergiving the GWAS description, e.g. name of study.
Author(s)
Juliane Manitz, Stefanie Friedrichs
Examples
# create gwas data object
data(pheno)
data(geno)
data(anno)
gwas <- new('GWASdata', pheno=pheno, geno=geno, anno=anno, desc="some study")
# show and summary methods
gwas
summary(gwas)
# SNPs and genes in pathway
GeneSNPsize(gwas)