In the biomedical environment, reproducibility is mainly taught in the setting of bench experiments. Data analyses description usually focus on basic measures such as mentioning the software version used, sharing the raw data, and occasionally providing a partial script. This presentation aims to showcase how we went from version labels to Guix and how it shaped our workflows to analyze various types of data, encompassing omics and targeted measurements. We will provide insights into how we effectively reported its utilization in our published manuscripts.