To be useful, scientific results must be reproducible and trustworthy. Data provenance—the history of data and how it was computed—underlies reproducibility of, and trust in, data analyses. Our work focuses on collecting data provenance from R scripts and providing tools that use the provenance to increase the reproducibility of and trust in analyses done in R. Specifically, our “End-to-end provenance tools” (“E2ETools”) use data provenance to: document the computing environment and inputs and outputs of a script’s execution; support script debugging and exploration; and explain differences in behavior across repeated executions of the same script. Use of these tools can help both the original author and later users of a script reproduce and trust its results.