PLoS Computational Biology (Jun 2017)

Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

  • C Victor Jongeneel,
  • Ovokeraye Achinike-Oduaran,
  • Ezekiel Adebiyi,
  • Marion Adebiyi,
  • Seun Adeyemi,
  • Bola Akanle,
  • Shaun Aron,
  • Efejiro Ashano,
  • Hocine Bendou,
  • Gerrit Botha,
  • Emile Chimusa,
  • Ananyo Choudhury,
  • Ravikiran Donthu,
  • Jenny Drnevich,
  • Oluwadamila Falola,
  • Christopher J Fields,
  • Scott Hazelhurst,
  • Liesl Hendry,
  • Itunuoluwa Isewon,
  • Radhika S Khetani,
  • Judit Kumuthini,
  • Magambo Phillip Kimuda,
  • Lerato Magosi,
  • Liudmila Sergeevna Mainzer,
  • Suresh Maslamoney,
  • Mamana Mbiyavanga,
  • Ayton Meintjes,
  • Danny Mugutso,
  • Phelelani Mpangase,
  • Richard Munthali,
  • Victoria Nembaware,
  • Andrew Ndhlovu,
  • Trust Odia,
  • Adaobi Okafor,
  • Olaleye Oladipo,
  • Sumir Panji,
  • Venesa Pillay,
  • Gloria Rendon,
  • Dhriti Sengupta,
  • Nicola Mulder

DOI
https://doi.org/10.1371/journal.pcbi.1005419
Journal volume & issue
Vol. 13, no. 6
p. e1005419

Abstract

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The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.