Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome

Garijo Verdejo, Daniel and Kinnings, Sarah and Xie, Li and Xie, Lei and Zhang, Yinliang and Bourne, Philip E. and Gil, Yolanda (2013). Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome. "Plos one" ; ISSN 1932-6203. https://doi.org/10.1371/journal.pone.0080278.

Description

Title: Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome
Author/s:
  • Garijo Verdejo, Daniel
  • Kinnings, Sarah
  • Xie, Li
  • Xie, Lei
  • Zhang, Yinliang
  • Bourne, Philip E.
  • Gil, Yolanda
Item Type: Article
Título de Revista/Publicación: Plos one
Date: 2013
ISSN: 1932-6203
Subjects:
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
UPM's Research Group: oeg
Creative Commons Licenses: None

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Abstract

How easy is it to reproduce the results found in a typical computational biology paper? Either through experience or intuition the reader will already know that the answer is with difficulty or not at all. In this paper we attempt to quantify this difficulty by reproducing a previously published paper for different classes of users (ranging from users with little expertise to domain experts) and suggest ways in which the situation might be improved. Quantification is achieved by estimating the time required to reproduce each of the steps in the method described in the original paper and make them part of an explicit workflow that reproduces the original results. Reproducing the method took several months of effort, and required using new versions and new software that posed challenges to reconstructing and validating the results. The quantification leads to “reproducibility maps” that reveal that novice researchers would only be able to reproduce a few of the steps in the method, and that only expert researchers with advance knowledge of the domain would be able to reproduce the method in its entirety. The workflow itself is published as an online resource together with supporting software and data. The paper concludes with a brief discussion of the complexities of requiring reproducibility in terms of cost versus benefit, and a desiderata with our observations and guidelines for improving reproducibility. This has implications not only in reproducing the work of others from published papers, but reproducing work from one’s own laboratory.

More information

Item ID: 21853
DC Identifier: http://oa.upm.es/21853/
OAI Identifier: oai:oa.upm.es:21853
DOI: 10.1371/journal.pone.0080278
Official URL: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0080278
Deposited by: Dr Oscar Corcho
Deposited on: 03 Dec 2013 12:35
Last Modified: 21 Apr 2016 12:38
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