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!
I'm not entirely sure if that's what you are asking for, but this post might be useful: Survival analysis of TCGA patients integrating gene expression (RNASeq) data