Literature DB >> 28510230

How to test bioinformatics software?

Amir Hossein Kamali1,2, Eleni Giannoulatou1,3, Tsong Yueh Chen4, Michael A Charleston5, Alistair L McEwan2, Joshua W K Ho6,7.   

Abstract

Bioinformatics is the application of computational, mathematical and statistical techniques to solve problems in biology and medicine. Bioinformatics programs developed for computational simulation and large-scale data analysis are widely used in almost all areas of biophysics. The appropriate choice of algorithms and correct implementation of these algorithms are critical for obtaining reliable computational results. Nonetheless, it is often very difficult to systematically test these programs as it is often hard to verify the correctness of the output, and to effectively generate failure-revealing test cases. Software testing is an important process of verification and validation of scientific software, but very few studies have directly dealt with the issues of bioinformatics software testing. In this work, we review important concepts and state-of-the-art methods in the field of software testing. We also discuss recent reports on adapting and implementing software testing methodologies in the bioinformatics field, with specific examples drawn from systems biology and genomic medicine.

Keywords:  Automated testing; Bioinformatics; Cloud-based testing; Quality assurance; Software testing

Year:  2015        PMID: 28510230      PMCID: PMC5425734          DOI: 10.1007/s12551-015-0177-3

Source DB:  PubMed          Journal:  Biophys Rev        ISSN: 1867-2450


  16 in total

1.  Mozilla plan seeks to debug scientific code.

Authors:  Erika Check Hayden
Journal:  Nature       Date:  2013-09-26       Impact factor: 49.962

2.  Computing: Scientific software needs quality control.

Authors:  Kieran Alden; Mark Read
Journal:  Nature       Date:  2013-10-24       Impact factor: 49.962

3.  Comparing simulation results of SBML capable simulators.

Authors:  Frank T Bergmann; Herbert M Sauro
Journal:  Bioinformatics       Date:  2008-06-25       Impact factor: 6.937

4.  Rule rewrite aims to clean up scientific software.

Authors:  Erika Check Hayden
Journal:  Nature       Date:  2015-04-16       Impact factor: 49.962

5.  Fast gapped-read alignment with Bowtie 2.

Authors:  Ben Langmead; Steven L Salzberg
Journal:  Nat Methods       Date:  2012-03-04       Impact factor: 28.547

6.  Testing and Validating Machine Learning Classifiers by Metamorphic Testing.

Authors:  Xiaoyuan Xie; Joshua W K Ho; Christian Murphy; Gail Kaiser; Baowen Xu; Tsong Yueh Chen
Journal:  J Syst Softw       Date:  2011-04-01       Impact factor: 2.829

7.  Scientific software development is not an oxymoron.

Authors:  Susan M Baxter; Steven W Day; Jacquelyn S Fetrow; Stephanie J Reisinger
Journal:  PLoS Comput Biol       Date:  2006-09-08       Impact factor: 4.475

8.  Verification and validation of bioinformatics software without a gold standard: a case study of BWA and Bowtie.

Authors:  Eleni Giannoulatou; Shin-Ho Park; David T Humphreys; Joshua W K Ho
Journal:  BMC Bioinformatics       Date:  2014-12-08       Impact factor: 3.169

9.  An innovative approach for testing bioinformatics programs using metamorphic testing.

Authors:  Tsong Yueh Chen; Joshua W K Ho; Huai Liu; Xiaoyuan Xie
Journal:  BMC Bioinformatics       Date:  2009-01-19       Impact factor: 3.169

10.  Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing.

Authors:  Jason O'Rawe; Tao Jiang; Guangqing Sun; Yiyang Wu; Wei Wang; Jingchu Hu; Paul Bodily; Lifeng Tian; Hakon Hakonarson; W Evan Johnson; Zhi Wei; Kai Wang; Gholson J Lyon
Journal:  Genome Med       Date:  2013-03-27       Impact factor: 11.117

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  8 in total

1.  Modelling, inference and big data in biophysics.

Authors:  Joshua W K Ho; Guy H Grant
Journal:  Biophys Rev       Date:  2017-07-30

Review 2.  Scalability and Validation of Big Data Bioinformatics Software.

Authors:  Andrian Yang; Michael Troup; Joshua W K Ho
Journal:  Comput Struct Biotechnol J       Date:  2017-07-20       Impact factor: 7.271

Review 3.  General guidelines for biomedical software development.

Authors:  Luis Bastiao Silva; Rafael C Jimenez; Niklas Blomberg; José Luis Oliveira
Journal:  F1000Res       Date:  2017-03-15

Review 4.  The State of Software for Evolutionary Biology.

Authors:  Diego Darriba; Tomáš Flouri; Alexandros Stamatakis
Journal:  Mol Biol Evol       Date:  2018-05-01       Impact factor: 16.240

5.  A preliminary computational outputs versus experimental results: Application of sTRAP, a biophysical tool for the analysis of SNPs of transcription factor-binding sites.

Authors:  Shirin Moradifard; Reza Saghiri; Parastoo Ehsani; Fatemeh Mirkhani; Mina Ebrahimi-Rad
Journal:  Mol Genet Genomic Med       Date:  2020-03-10       Impact factor: 2.183

6.  A large-scale analysis of bioinformatics code on GitHub.

Authors:  Pamela H Russell; Rachel L Johnson; Shreyas Ananthan; Benjamin Harnke; Nichole E Carlson
Journal:  PLoS One       Date:  2018-10-31       Impact factor: 3.240

7.  TBX2 Identified as a Potential Predictor of Bone Metastasis in Lung Adenocarcinoma via Integrated Bioinformatics Analyses and Verification of Functional Assay.

Authors:  Huajian Yu; Fangyu Zhao; Jing Li; Kechao Zhu; Hechun Lin; Zhen Pan; Miaoxin Zhu; Ming Yao; Mingxia Yan
Journal:  J Cancer       Date:  2020-01-01       Impact factor: 4.207

8.  Improving bioinformatics software quality through incorporation of software engineering practices.

Authors:  Adeeb Noor
Journal:  PeerJ Comput Sci       Date:  2022-01-05
  8 in total

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