Open harrsha4 opened 1 month ago
Thank you for your feedback. Currently, the mlr
method does require a covariate matrix. We will need to add the option for the mlr
method to run without a covariate matrix.
In the meantime, one option is to run the analysis using the correlation method (corr
), which will also test for a relationship between gene expression and methylation levels.
tecpg run corr --help
Usage: tecpg run corr [OPTIONS]
Calculate the pearson correlation coefficient.
Calculate the pearson correlation coefficient with methylation and gene
expression matrices. Optional compute and save chunking to avoid GPU and CPU
memory limits.
Options:
-c, --chunks INTEGER [default: 0]
-s, --save-chunks INTEGER [default: 0]
--help Show this message and exit.
Thank you for the reply. Another question, if possible: If you have a 3 cohort dataset that you want to include as a covariate, would we need to convert them to numeric and treat them as a numeric variable, or could we maintain a categorical variable?
Currently, categorical covariates must be converted to numeric to be supported.
Thank you for this wonderful tool. The regression command usually requires covariates to run the model. Is there an option to exclude the covariates when running the regression?