How to make a survival plot for a gene between High expression and low expression samples?
Hi,
I have downloaded TCGA data for lung cancer. It is counts data. I want to make survival plot for a specific gene between high expression and low expression samples. I want to make both Overall survival and Disease free survival plots. It should look something like this Kaplan-Meier survival analysis of OS (P < 0.001, log-rank) and DFS (P < 0.001, log-rank) rate in 144 patients based on the expression level of SNHG20 expression
How to divide the samples into high and low expression samples based on expression of single gene? I have counts data. Is there any cutoff for that?
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You could plot the data and see how it spreads and use this do define the cutoff (e.g. if you notice there is clear separation into 2 groups). Another approach might be to use z-score and take +-1-2 score as high and low..
Based on z-score, so +1 and +2 are high, -1 and -2 are low? And for this survival do I also need to consider normal samples? or only tumor samples?
Yes, you can try a cutoff on 1 or 2 and see how it looks like ( for a two sided distribution the critical Z score values when using a 95% confidence level are -1.96 and +1.96). This task could be easily accomplished using cbioportal.org
I would plot cancer and normal on different charts (not sure there is point in showing a survival chart for normal individuals).
Ok. Thankyou. then I will convert counts data to logCPM and then to Z-score. From that samples with values less than -1.96 are low and samples with more than +1.96 are high and then make a survival plot for that.