Rationale here is that it is informative to see genetic perturbations that are both negatively and positively correlated with the query signature.
For example, in the SJIA lung nanostring dataset, IFNy ligand and over-expression are among the top few most positively correlated signatures. This supports Alexi and Grants hypothesis regarding the drivers of the disease.
Rationale here is that it is informative to see genetic perturbations that are both negatively and positively correlated with the query signature.
For example, in the SJIA lung nanostring dataset, IFNy ligand and over-expression are among the top few most positively correlated signatures. This supports Alexi and Grants hypothesis regarding the drivers of the disease.