assocCoxPH: Cox proportional hazards

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/assocCoxPH.R

Description

Fits Cox proportional hazards model

Usage

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assocCoxPH(genoData,
           event,
           time.to.event,
           gene.action = c("additive", "dominant", "recessive"),
           covar = NULL,
           ivar = NULL,
           strata = NULL,
           scan.exclude = NULL,
           effectAllele = c("minor", "alleleA"),
           snpStart = NULL,
           snpEnd = NULL,
           block.size = 5000,
           verbose = TRUE)

Arguments

genoData

a GenotypeData object

event

name of scan annotation variable in genoData for event to analyze (chould be coded 0/1 or FALSE/TRUE)

time.to.event

name of scan annotation variable in genoData for time to event

gene.action

"additive" coding sets the marker variable for homozygous minor allele samples = 2, heterozygous samples = 1, and homozygous major allele samples = 0. "dominant" coding sets the marker variable for homozygous minor allele samples = 2, heterozygous samples = 2, and homozygous major allele samples = 0. "recessive" coding sets the marker variable for homozygous minor allele samples = 2, heterozygous samples = 0, and homozygous major allele samples = 0. (If effectAllele="alleleA", the coding reflects alleleA instead of the minor allele.)

covar

a vector of the names of the covariates to adjust for (columns in the scan annotation of genoData)

ivar

the name of the variable in covar to include as an interaction with genotype

strata

a vector of names of variables to stratify on for a stratified analysis

scan.exclude

a vector of scanIDs for scans to exclude

effectAllele

whether the effects should be returned in terms of the minor allele for the tested sample (effectAllele="minor") or the allele returned by getAlleleA(genoData) (effectAllele="alleleA"). If the minor allele is alleleB for a given SNP, the difference between these two options will be a sign change for the beta estimate.

snpStart

index of the first SNP to analyze, defaults to first SNP

snpEnd

index of the last SNP to analyze, defaults to last SNP

block.size

number of SNPs to read in at once

verbose

logical for whether to print status updates

Details

This function performs Cox proportional hazards regression of a survival object (using the Surv function) on SNP genotype and other covariates. It uses the coxph function from the R survival library.

It is recommended to filter results returned using 2*MAF*(1-MAF)*n.events > 75 where MAF = minor allele frequency and n.events = number of events. This filter was suggested by Ken Rice and Thomas Lumley, who found that without this requirement, at threshold levels of significance for genome-wide studies, Cox regression p-values based on standard asymptotic approximations can be notably anti-conservative.

Note: Y chromosome SNPs must be analyzed separately because they only use males.

Value

a data.frame with some or all of the following columns:

snpID

the snpIDs

chr

chromosome SNPs are on

n

number of samples used to analyze each SNP

n.events

number of events in complete cases for each SNP

effect.allele

which allele ("A" or "B") is the effect allele

EAF

effect allele frequency

MAF

minor allele frequency

filter

TRUE if SNP passes the MAF filter (2*MAF*(1-MAF)*n.events > 75)

Est

beta estimate for genotype

SE

standard error of beta estimate for the genotype

z.Stat

z statistic for association

z.pval

p-value for association

GxE.Stat

Likelihood ratio test statistic for the genotype*ivar interaction parameter

GxE.pval

p-value for the likelihood ratio test statistic

Author(s)

Cathy Laurie, Matthew Conomos, Stephanie Gogarten

See Also

GenotypeData, coxph

Examples

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library(GWASdata)
data(illuminaScanADF)
scanAnnot <- illuminaScanADF

# exclude duplicated subjects
scan.exclude <- scanAnnot$scanID[scanAnnot$duplicated]

# create some variables for the scans
scanAnnot$sex <- as.factor(scanAnnot$sex)
scanAnnot$age <- rnorm(nrow(scanAnnot), mean=40, sd=10)
scanAnnot$event <- rbinom(nrow(scanAnnot), 1, 0.4)
scanAnnot$ttoe <- rnorm(nrow(scanAnnot), mean=100, sd=10)

# create data object
gdsfile <- system.file("extdata", "illumina_geno.gds", package="GWASdata")
gds <- GdsGenotypeReader(gdsfile)
genoData <-  GenotypeData(gds, scanAnnot=scanAnnot)

res <- assocCoxPH(genoData,
                  event="event", time.to.event="ttoe",
  		  covar=c("sex", "age"),
  		  scan.exclude=scan.exclude,
  		  snpStart=1, snpEnd=100)

close(genoData)

GWASTools documentation built on May 25, 2018, 6:01 p.m.