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Big biomedical data create exciting opportunities for discovery but make it difficult to capture analyses and outputs in forms that are findable, accessible, interoperable, and reusable (FAIR). In response, we describe tools that make it easy to capture, and assign identifiers to, data and code throughout the data lifecycle. We illustrate the use of these tools via a case study involving a multi- step analysis that creates an atlas of putative transcription factor binding sites from terabytesdoi:10.5281/zenodo.1484403 fatcat:mqztdeowdff6tb4vpy7km54rn4