In many biological experiments, due to gene-redundancy or distributed backup mechanisms, there are no visible effects on the functionality of the organism when a gene is knocked out or down. In such cases there is apparently no counterfactual dependence between the gene and the phenotype in question, although intuitively the gene is causally relevant. Due to relativity of causal relations to causal models, we suggest that such cases can be handled by changing the resolution of the causal model that represents the system. By decreasing the resolution of our causal model, counterfactual dependencies can be established at a higher level of abstraction. By increasing the resolution, stepwise causal dependencies of the right kind can serve as a sufficient condition for causal relevance. Finally, we discuss how introducing a temporal dimension in causal models can account for causation in cases of non-modular systems dynamics.