A Baseline Evaluation of Bioinformatics Capacity in Tanzania Reveals Areas for Training - Sangeda, Raphael Zozimus; Mwakilili, Aneth David; Masamu, Upendo; Nkya, Siana; Mwita, Liberata Alexander; Massawe, Deogracious Protas; Lyantagaye, Sylvester Leonard; Makani, Julie (Frontiers in Education, 2021)
Due to the insufficient human and infrastructure capacity to use novel genomics and bioinformatics technologies, Sub-Saharan Africa countries have not entirely ripped the benefits of these technologies in health and other sectors. The main objective of this study was to map out the interest and capacity for conducting bioinformatics and related research in Tanzania. The survey collected demographic information like age group, experience, seniority level, gender, number of respondents per institution, number of publications, and willingness to join the community of practice. The survey also investigated the capacity of individuals and institutions about computing infrastructure, operating system use, statistical packages in use, the basic Microsoft packages experience, programming language experience, bioinformatics tools and resources usage, and type of analyses performed. Moreover, respondents were surveyed about the challenges they faced in implementing bioinformatics and their willingness to join the bioinformatics community of practice in Tanzania. Out of 84 respondents, 50 (59.5%) were males. More than half of these 44 (52.4%) were between 26-32 years. The majority, 41 (48.8%), were master's degree holders with at least one publication related to bioinformatics. Eighty (95.2%) were willing to join the bioinformatics network and initiative in Tanzania. The major challenge faced by 22 (26.2%) respondents was the lack of training and skills. The most used resources for bioinformatics analyses were BLAST, PubMed, and GenBank. Most respondents who performed analyses included sequence alignment and phylogenetics, which was reported by 57 (67.9%) and 42 (50%) of the respondents, respectively. The most frequently used statistical software packages were SPSS and R. A quarter of the respondents were conversant with computer programming. Early career and young scientists were the largest groups of responders engaged in bioinformatics research and activities across surveyed institutions in Tanzania. The use of bioinformatics tools for analysis is still low, including basic analysis tools such as BLAST, GenBank, sequence alignment software, Swiss-prot and TrEMBL. There is also poor access to resources and tools for bioinformatics analyses. To address the skills and resources gaps, we recommend various modes of training and capacity building of relevant bioinformatics skills and infrastructure to improve bioinformatics capacity in Tanzania.