Data Management Plan

As researchers of fundamental science we truly believe that we should make research more open to participation and improvement Therefore we will implement a complete set of open science policies that will enclose reproducible research and science tools following the FAIR principles Findable Accessible Interoperable and Reusable All highthroughput sequencing data produced in the lab of Michael Potente will be submitted and shared through consensual large repositories such as Gene Expression Omnibus httpswwwncbinlmnihgovgeo or Short Sequence Read Archive httpswwwncbinlmnihgovsra Here processed data in standard format files will be provided to facilitate the reuse of the data This will be backed by complete and detailed information about sample and library preparation sequencing details and bioinformatics analyses We will provide extensive technical details and share experimental protocols used for genetic manipulations in all our outputs manuscripts thesis etc Moreover our computational approaches will be mostly based on opensource programming languages eg Python R and Bash scripts and will be shared with the community through our publications and open science platforms eg Github Zenodo Here we will enforce the reproducibility of the analyses building frameworks with Docker Images The host lab has been applying such procedures in other bioinformatics pipelines available in GitHub httpsgithubcomcomicsfct and as Docker Images httpshubdockercomuargrosso Our findings will be published following an Open Access philosophy meaning that they will be accessible online free of charge by any user with no technical obstacles Potential MSc dissertations in the framework of this project will be shared using the proper resources of our universities