Using Open Source Tools for Analysis of the Mutation Rate of African Cassava Mosaic Virus

Main Article Content

Grey Chibawe
Lillian Mzyece
Mayumbo Nyirenda
Jackson Phiri

Abstract

Popular tools used in studies in life sciences are often costly. This often pauses challenges to researchers in spite of the fact that research continues to be a key to the successful systematic development of new knowledge and a fundamental aspect to the usefulness of all higher education. Particularly, higher education also aims to advance, create and disseminate knowledge through research. Such critical studies like mutation studies therefore require affordable and fast results yielding software. In such research, open source software tools become handy in place of expensive proprietary tools. In order to provide alternative software tools for research, we decided to use a case study of the mutation of the African Cassava Mosaic Virus (ACMV) done by researchers in Zambia. The study of ACMV mutation is hampered by fragmented and non-user-friendly tools, which are currently available. A number of the tools used also depend on network connection, especially the Internet, to access and analyze data. To help alleviate this problem this research proposes the use of open source libraries in biopython to generate cost efficient and user-friendly solutions. Additionally, we propose the use of an open standard using XML as a standard protocol to share data between applications or stages in genomic data analysis of the ACMV. In our strife to provide open source solutions we analysed various tools and noted that biopython is quite popular. During our study of biopython our initial results show that it’s possible to use free tools to analyze data in the life sciences and consequently reduce the time and cost required to analyze ACMV. Based on this case study we propose the adoption of such open source libraries in order to make research much more affordable for scientists in the life sciences for researches that operate within a constrained budget.

Article Details

How to Cite
Chibawe, G., Mzyece, L., Nyirenda, M., & Phiri, J. (2018). Using Open Source Tools for Analysis of the Mutation Rate of African Cassava Mosaic Virus. Zambia ICT Journal, 2(1), 44-56. https://doi.org/10.33260/zictjournal.v2i1.50
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Articles
Author Biographies

Grey Chibawe, University of Zambia

Department of Computer Science
P.O. Box 32375-Lusaka, Zambia

Lillian Mzyece, University of Zambia

Department of Computer Science
P.O. Box 32375-Lusaka, Zambia

Mayumbo Nyirenda, University of Zambia

Department of Computer Science
P.O. Box 32375-Lusaka, Zambia

Jackson Phiri, University of Zambia

Department of Computer Science
P.O. Box 32375-Lusaka, Zambia