summary.famStudy: Summary function for objects of class famStudy

Description

Summary function for objects of class famStudy, i.e. objects returned by the sim_RVstudy function.

Usage

# S3 method for famStudy
summary(object, ...)

Arguments

object

An object of class famStudy, returned by the sim_RVstudy function.

...

additional arguments passed to other methods.

Value

fam_allele_count

A matrix that contains counts of the SNVs shared by the disease-affected relatives in each pedigree.

pathway_count

A data frame that catalogs the SNVs shared among disease-affected study participants. See details.

Details

The summary.famStudy function returns a list containing two items. The first item, fam_allele _count, is a matrix that contains counts of the SNVs shared by the disease-affected relatives in each pedigree. This matrix will contain a row of counts for each pedigree in the supplied famSutdy object. The first column in fam_allele_count is named FamID and identifies each pedigree by their family identification number. The remaining columns in fam_allele_count are named according to the respective marker names of the shared SNVs.

The second item returned by summary.famStudy is a data frame named pathway_count, which catalogs the SNVs shared among disease-affected study participants. This data frame contains the following variables:

name	type	description
`chrom`	numeric	chromosome identification number
`position`	numeric	the position of the SNV
`marker`	character	a unique character identifier for the SNV
`total`	numeric	the number of SNV copies observed in disease-affected study participants.
`is_crv`	logical	identifies causal rare variants (cRVs) as `TRUE`
`pathwaySNV`	logical	identifies SNVs located within the pathway of interest as `TRUE`.

Please note, the variable pathwaySNV is omitted when missing from the SNV_map data frame in the famStudy object. See sim_RVstudy for more details.

Examples

Run this code

# NOT RUN {
library(SimRVSequences)

# load pedigree, haplotype, and mutation data
data(study_peds)
data(EXmuts)
data(EXhaps)

# create variable is_CRV in EXmuts to identify the causal
# rare variants from which to sample familial cRVs.
EXmuts$is_CRV = FALSE
EXmuts$is_CRV[c(26, 139, 223, 228, 472)] = TRUE

# supply required inputs to the sim_RVstudy function
seqDat = sim_RVstudy(ped_files = study_peds,
                     SNV_data = SNVdata(Haplotypes = EXhaps,
                                        Mutations = EXmuts))

# to count the number of SNVs shared by the disease-affected
# relatives in each pedigree, supply the output returned by
# sim_RVstudy to the summary function
summary(seqDat)


# }