Entering edit mode
4 months ago
As the title informs, I'm currently working with a high dimensionality DNA methylation data. After performing batch correction, normalization and missing value imputation. I'm left with a significantly high dimensionality data, so I was looking for dimensionality reduction techniques and came across this literature. So as stated in this work I tried to perform univariate cox analysis to reduce the feature count but I'm not sure what cut-off value should I use for q-value so that I can eliminate features which are false positive and at the mean time not increasing false negatives.
Thank you for reading through my thread, if you need any additional detail please feel free to ask me. I'll respond within few minutes.
