uni.cox: uni.cox
In margarethannum/gnomeR: What the Package Does (One Line, Title Case)

Description Usage Arguments Value Examples

Performs univariate cox proportional hazard model on every feature

1	uni.cox(X, surv.dat, surv.formula, filter = 0, genes = NULL)

`X`	Matrix/surv.datframe of genomic features, continuous or binary (note cannot handle categorical surv.dat for the moment).
`surv.dat`	a surv.dat frame containing the survival information. This can be made of 2 or 3 columns. 1 or 2 for time, and one for status (where 1 is event and 0 is no event).
`surv.formula`	a survival formula with names matching those in surv.dat eg: Surv(time,status)~.
`filter`	a numeric value between 0 and 1 (1 not included) that is the lower bound for the proportion of patients having a genetic event (only for binary features). All features with an event rate lower than that value will be removed. Default is 0 (all features included).
`genes`	a character vector of gene names that will be the only ones to be kept. Default is NULL, all genes are used.

tab A table of all the fits performed sorted by adjusted pvalues.

p An interactive plot of log(pvalue) by hazard ration.

KM List of survival plots of the top 10 most significant genes

library(gnomeR)
patients <- unique(clin$DMPID)[1:100]
mut.only <- create.bin.matrix(patients = patients,maf = mut)
gen.dat <- mut.only$mut
surv.dat <-clin[match(patients,clin$DMPID),match(c("time","status") ,colnames(clin))]
surv.dat$status <- ifelse(surv.dat$status == "DECEASED",1,0)
surv.dat$time <- as.numeric(as.character(surv.dat$time))

cox.fits <- uni.cox(X = gen.dat,surv.dat = surv.dat, surv.formula = Surv(time,status)~.,filter = 0.03)