require(Hmisc)
h <- csv.get('new_feature_table.csv')
xless(contents(h))
n <- names(h)
n <- paste('mz',round(as.numeric(substring(n, 2))),sep='')
names(h)[9:ncol(h)] <- n[9:ncol(h)]
names(h)
Save(h)

f <- coxph(Surv(Survival, Status=='DOD') ~ Age + Gender, data=h)
f

require(glmpath)
h$Gender <- 1*(h$Gender == 'Male')
x <- as.matrix(h[7:ncol(h)])
xless(x[1:10,])
data <- list(x=x, time=h$Survival, status=1*(h$Status == 'DOD'))
g <- coxpath(data, nopenalty.subset=1:2, method='efron')
xless(summary(g))
plot(g)

cv <- cv.coxpath(data, method='efron')             
xless(cv)

g2 <- coxpath(data, method='efron')
xless(summary(g2))
plot(g2)
xless(unclass(g2))