2020/06/03 by Ali Salari, Gregory Kiar, Salari, Ali +8
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · Engineering · Medicine · #Medical Imaging Techniques and Applications #Research Data Management Practices #Scientific Computing and Data Management #eess.IV #q-bio.QM
paper · pdf · doi:10.48550/arxiv.2006.04684
10 pages, 6 figures, 2 tables
arxiv created 2020/09/29 · arxiv updated 2020/09/30
Data analysis pipelines are known to be impacted by computational conditions, presumably due to the creation and propagation of numerical errors. While this process could play a major role in the current reproducibility crisis, the precise causes of such instabilities and the path along which they propagate in pipelines are unclear. We present Spot, a tool to identify which processes in a pipeline create numerical differences when executed in different computational conditions. Spot leverages system-call interception through ReproZip to reconstruct and compare provenance graphs without pipeline instrumentation. By applying Spot to the structural pre-processing pipelines of the Human Connectome Project, we found that linear and non-linear registration are the cause of most numerical instabilities in these pipelines, which confirms previous findings.