Ten simple rules to increase computational skills among biologists with Code Clubs

For most biologists, the ability to generate data has outpaced the ability to analyze those data. High throughput data comes to us from DNA and RNA sequencing, flow cytometry, metabolomics, molecular screens, and more. Although some accept the approach of compartmentalizing data generation and data analysis, we have found scientists feel empowered when they can both ask and answer their own biological questions [1]. In our experience performing microbiome research, it is more common to find exceptional bench scientists who are inexperienced at analyzing large data sets than to find the reverse. Of course, this raises a challenge: how do we train bench scientists to effectively answer biological questions with these larger data sets? Copyright: © 2020 Hagan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.