Systematically Examining Reproducibility: A Case Study for High Throughput Sequencing
Автор: ZB MED
Загружено: 2025-04-28
Просмотров: 39
Описание:
Computational reproducibility is defined as achieving consistent computational results using the same input data, computational steps, methods, codes and analysis conditions. It is a key factor in biomedical research - particularly in critical domains like human health because only if analyses are reproducible and repeatable can scientific results create trust, be verified and ultimately lead to research progress. What can impair this reproducibility is the fact that the individual components that make up research objects can change over time.
Meznah Aloqalaa, PhD candidate at the University of Manchester in the eScience Lab at the department of computer science, investigates this topic in her PhD research, titled "An Investigation into the Reproducibility of Research Objects".
In this talk she presents the PRIMAD model, a conceptual framework for describing computational experiments for reproducibility purposes. In her study PRIMAD is used to systematically review the BioCompute Object (BCO), a framework for documenting pipelines that is for example used by the USA's Food and Drug Administration (FDA), for depth and coverage.
#research #computationalbiology
Content:
00:00 Introduction
01:13 Computational Reproducibility
01:52 PRIMAD Model
04:45 BioCompute Object (BCO)
07:35: Study: Systematically Examining Reproducibility
10:07 Results for BCO
12:48 Results for PRIMAD
14:11 Conclusions and next steps on the PRIMAD model
Further information:
▶️ University of Manchester in the eScience Lab at the department of computer science: https://esciencelab.org.uk/
▶️ Systematically Examining Reproducibility: A Case Study for High Throughput Sequencing using the PRIMAD Model and BioCompute Object: https://doi.org/10.48550/arXiv.2412.0...
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ZB MED – Informationszentrum Lebenswissenschaften wird gefördert durch das Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen.
Dieses Video ist lizenziert unter einer Creative Commons Namensnennung 4.0 International Lizenz - CC BY 4.0.
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