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File-based localization of numerical perturbations in data analysis pipelines.

Author(s): Salari A, Kiar G, Lewis L, Evans AC, Glatard T

BACKGROUND: Data analysis pipelines are known to be affected by computational conditions, presumably owing to the creation and propagation of numerical errors. While this process could play a major role in the current reproducibility crisis, the precise cau...

Article GUID: 33269388
Comparing perturbation models for evaluating stability of neuroimaging pipelines.

Author(s): Kiar G, de Oliveira Castro P, Rioux P, Petit E, Brown ST, Evans AC, Glatard T

With an increase in awareness regarding a troubling lack of reproducibility in analytical software tools, the degree of validity in scientific derivatives and their downstream results has become unclear. The nature of reproducibility issues may vary across ...

Article GUID: 32831546
Boutiques: a flexible framework to integrate command-line applications in computing platforms.

Author(s): Glatard T, Kiar G, Aumentado-Armstrong T, Beck N, Bellec P, Bernard R, Bonnet A, Brown ST, Camarasu-Pop S, Cervenansky F, Das S, Ferreira da...

Gigascience. 2018 05 01;7(5): Authors: Glatard T, Kiar G, Aumentado-Armstrong T, Beck N, Bellec P, Bernard R, Bonnet A, Brown ST, Camarasu-Pop S, Cervenansky F, Das S, Ferreira da Silva R, Flandin...

Article GUID: 29718199
A Serverless Tool for Platform Agnostic Computational Experiment Management.

Author(s): Kiar G, Brown ST, Glatard T, Evans AC

Front Neuroinform. 2019;13:12 Authors: Kiar G, Brown ST, Glatard T, Evans AC

Article GUID: 30890927
Title:File-based localization of numerical perturbations in data analysis pipelines.
Authors:Salari A,  Kiar G,  Lewis L,  Evans AC,  Glatard T
Link:https://www.ncbi.nlm.nih.gov/pubmed/33269388
DOI:10.1093/gigascience/giaa106
Category:Gigascience
PMID:33269388
Dept Affiliation: ENCS
1 Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada.
2 Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.
3 Montreal Neurological Institute, McGill University, Montreal, QC, Canada.

Description:

File-based localization of numerical perturbations in data analysis pipelines.

Gigascience. 2020 Dec 02; 9(12):

Authors: Salari A, Kiar G, Lewis L, Evans AC, Glatard T

Abstract

BACKGROUND: Data analysis pipelines are known to be affected by computational conditions, presumably owing 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.

METHOD: 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.

RESULTS: 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.

PMID: 33269388 [PubMed - in process]