Correction: Ten simple rules for organizing a bioinformatics training course in low- and middle-income countries.

[This corrects the article DOI: 10.1371/journal.pcbi.1009218.].

Data Management Plans in the genomics research revolution of Africa: Challenges and recommendations.

Drafting and writing a data management plan (DMP) is increasingly seen as a key part of the academic research process. A DMP is a document that describes how a researcher will collect, document, describe, share, and preserve the data that will be generated as part of a research project. The DMP illustrates the importance of utilizing best practices through all stages of working with data while ensuring accessibility, quality, and longevity of the data. The benefits of writing a DMP include compliance with funder and institutional mandates; making research more transparent (for reproduction and validation purposes); and FAIR (findable, accessible, interoperable, reusable); protecting data subjects and compliance with the General Data Protection Regulation (GDPR) and/or local data protection policies. In this review, we highlight the importance of a DMP in modern biomedical research, explaining both the rationale and current best practices associated with DMPs. In addition, we outline various funders' requirements concerning DMPs and discuss open-source tools that facilitate the development and implementation of a DMP. Finally, we discuss DMPs in the context of African research, and the considerations that need to be made in this regard.

A new macromedusa from the coast of Mozambique: Aurelia mozambica sp. nov. (Scyphozoa: Ulmaridae).

A new species of the cosmopolitan jellyfish genus Aurelia is described from the coastal waters of Mozambique using a combination of morphological, meristic and genetic information (COI and 18S). The species can be separated from congeners that have been recently described by a combination of bell shape, number of canal origins and anastomoses, and the shape of the manubrium and oral arms. Three types of nematocysts are present in the tissues of both the bell margin and oral arms, and this description of the cnidome will allow for future comparison. Pairwise genetic comparisons showed a mean COI divergence of 4.8% within the group, and a mean divergence ranging between 15% and 22% with all other species of Aurelia.

Using a multiple-delivery-mode training approach to develop local capacity and infrastructure for advanced bioinformatics in Africa.

With more microbiome studies being conducted by African-based research groups, there is an increasing demand for knowledge and skills in the design and analysis of microbiome studies and data. However, high-quality bioinformatics courses are often impeded by differences in computational environments, complicated software stacks, numerous dependencies, and versions of bioinformatics tools along with a lack of local computational infrastructure and expertise. To address this, H3ABioNet developed a 16S rRNA Microbiome Intermediate Bioinformatics Training course, extending its remote classroom model. The course was developed alongside experienced microbiome researchers, bioinformaticians, and systems administrators, who identified key topics to address. Development of containerised workflows has previously been undertaken by H3ABioNet, and Singularity containers were used here to enable the deployment of a standard replicable software stack across different hosting sites. The pilot ran successfully in 2019 across 23 sites registered in 11 African countries, with more than 200 participants formally enrolled and 106 volunteer staff for onsite support. The pulling, running, and testing of the containers, software, and analyses on various clusters were performed prior to the start of the course by hosting classrooms. The containers allowed the replication of analyses and results across all participating classrooms running a cluster and remained available posttraining ensuring analyses could be repeated on real data. Participants thus received the opportunity to analyse their own data, while local staff were trained and supported by experienced experts, increasing local capacity for ongoing research support. This provides a model for delivering topic-specific bioinformatics courses across Africa and other remote/low-resourced regions which overcomes barriers such as inadequate infrastructures, geographical distance, and access to expertise and educational materials.