bMINTY: enabling reproducible management of high-throughput sequencing analysis results and their metadata

Due to the large scale of high-throughput sequencing data generation, the community has established standards that promote Findable, Accessible, Interoperable and Reusable (FAIR) science. However, critical obstacles remain since best practices are not consistently enforced, with essential information being fragmented across methods, supplementary materials, and public repositories. When attempting to reproduce scientific findings or reuse published data, researchers often avoid analyzing sequencing data from the ground up. Instead, they prefer to use post-alignment information (e.g. gene expression matrices). However, existing repositories and workflow-oriented solutions rarely provide a single, portable, queryable resource that integrates this information with the metadata required for downstream reuse. We introduce bMINTY, a locally deployed web application with an intuitive user interface, for structured management of post-alignment workflow data outputs. bMINTY supports metadata for studies, assays, and analysis assets, including workflows, genome annotation versions, and cell-level entities for single-cell assays. Users may export query results in RO-Crate format, providing machine readable data packages and metadata. These packages can be included as supplementary material with each publication, accompanied by analysis code deposited in public repositories for downstream ad hoc analyses. Together, these practices can promote transparency, efficient FAIR-aligned reuse of published post-alignment data.