efst | Python Encrypted FS tools
kandi X-RAY | efst Summary
kandi X-RAY | efst Summary
Python Encrypted FS tools
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of efst
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QUESTION
I am a student conducting a gene expression survival analysis in R. I have the expression data for 249 patients, and I am using 6,000 genes as well as their event-free survival times and vital state as response variables. When I tried to run the Cox regression on my dataset, I got extremely strange results (p-values of 0.00 and strange hazard ratios). I have checked over my code multiple times, but I am not able to catch my mistake (when I tried earlier with just one gene, it worked fine, but when I try to test multiple genes using the '.' function, I am not getting porper results). I would highly appreciate any help and have attached both my code and output! Let me know if more information is needed.
...ANSWER
Answered 2020-Feb-25 at 02:40Except for the first two coefficients (EFST
and Status
), the coefficients for all other genes are either extremely small or extremely large, leading to very large negative/positive t-statistics, which explains the p-values you're seeing.
I'm not exactly sure I understood what you're doing. Wouldn't regressing on 6,000 genes in your 249 patients data mean that you're having way more parameters than observations?
In which case, you're running into overfitting issues which would explain the parameter estimates.
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