If you run the following code, you will have a data frame `real.dat` which has 1063 samples for 20531 genes. There are 2 extra columns named `time` and `event` where `time` is the survival time and `event` is `death` in case of `1` and `0` in case of `censored`. lung.dat <- read.table("genomicMatrix_lung") lung.clin.dat <- read.delim("clinical_data_lung") # For clinical data, get only rows which do not have NA in column "X_EVENT" lung.no.na.dat <- lung.clin.dat[!is.na(lung.clin.dat$X_EVENT), ] # Getting the transpose of main lung cancer data ge <- t(lung.dat) # Getting a vector of all the id's in the clinical data frame without any 'NA' values keep <- lung.no.na.dat$sampleID # getting only the samples(persons) for which we have a value rather than 'NA' values real.dat <- ge[ge[, 1] %in% keep, ] # adding the 2 columns from clinical data to gene expression data keep_again <- real.dat[, 1] temp_df <- lung.no.na.dat[lung.no.na.dat$sampleID %in% keep_again, ] # naming the columns into our gene expression data col_names <- ge[1, ] colnames(real.dat) <- col_names dd <- temp_df[, c('X_TIME_TO_EVENT', 'X_EVENT')] real.dat <- cbind(real.dat, dd) # renaming the 2 new added columns colnames(real.dat)[colnames(real.dat) == 'X_TIME_TO_EVENT'] <- 'time' colnames(real.dat)[colnames(real.dat) == 'X_EVENT'] <- 'event' I want to get the univariate Cox regression p-value for each gene in the above data frame. Now, when I try to run the `coxph` function from the `survival` package even for one gene, it shows the following error - `> coxph(Surv(time, event) ~ HIF3A, real.dat) Error in fitter(X, Y, strats, offset, init, control, weights = weights, : NA/NaN/Inf in foreign function call (arg 6) In addition: Warning message: In fitter(X, Y, strats, offset, init, control, weights = weights, : Ran out of iterations and did not converge` What am I doing wrong here? You can download the data from [here](https://drive.google.com/open?id=0B2p9dpw7AL_zMTNXR1JwRW1KRmM).