Hey guy,

I've recently been using an online analysis tool based on tcga called http://www.oncolnc.org It's so cool! With TCGA expression data and the patient follow-up data, this online tool can actually create a list of gene, with these 'p-values'https://ibb.co/hpOyrQ and stuffs,and all the data was ranked by p-value, and the smaller the p-value, the higher the rank and also the greater connection with the overall survival. https://ibb.co/jJ06d5 For example, the 1st ranked gene ITGA is significantly related with a low log-rank p-value K-M plot. If you don't know it, please try it, its very handy!

I'm thinking, say, I have 50 microarray data and the patients follow-up information. Is there any way by using R or online tool to get these statistical results as the table showed in the first figure, which can definitely provide insight into some interesting gene.

What I currently know is to calculate the specific KM-plot for a selected gene by the median of expression data ONE BY ONE. That something old like dirt I believe:(

Any master here share some information about this analysis? This would be with great help! Really appreciate it!

Thanks in advance. And nice weekends!