Workshop dates: Sunday, 8 October 2017 [post doc/ early career scientist stream] (08:30-17:15); Monday, 9 October 2017 [student stream] (08:30-17:00)

Venue: Ocean Room, Radisson Blu Hotel, Dakar, Senegal

Workshop organisers and sponsors: H3ABioNet, NIH Common Fund

Workshop trainers and support: Nicola Mulder, Sumir Panji, Ayton Meintjes, Scott Hazelhurst, Fourie Joubert, Alia Benkahla and Faisal Fadlemola.

Course Overview: This interactive workshop will provide an overview of data management, analysis and submission for H3Africa projects. It also provides an opportunity for Data Support Working Group members, who represent the H3Africa projects to engage with H3ABioNet and discuss their needs.

Intended Audience: This workshop is aimed at Data Support Working Group members who should be the H3Africa project data managers, data analysts or bioinformaticians. It is important that the attendees have knowledge of the data being generated by their H3Africa projects and information about the project’s data analysis plan.

Syllabus: Participants will discuss their current data plans and challenges. Lectures will be given on Clinical data collection & storage, overview of GWAS/NGS/microbiome processing, downstream analysis (Variant annotation, meta-analysis, structure, ancGWAS), Data transfer considerations, security, data processing options, and H3Africa Archive and EGA submission. This will be followed by discussion on developing data management plans (with reference to the article: Michener WK (2015) Ten Simple Rules for Creating a Good Data Management Plan. PLoS Comput Biol 11(10): e1004525), and interactive sessions discussing specific projects.

Prerequisites: Participants should complete the survey at: H3Africa Data Support workshop planning survey - Senegal 2016. One survey needs to be completed per H3Africa project.

Objectives:

• Participants will learn how to develop a data management plan.
• Participants will gain basic knowledge on issues around data security & submission.
• Participants should come out understanding what considerations there are for their own data analysis, storage and compute requirements.
• Participants will be able to engage with H3ABioNet on their needs and issues.

Workshop limitations: This workshop will provide a foundation for continued learning in the handling of H3Africa project data. It will not make one an expert in specific data  analysis pipelines.

Workshop Program

Attachments:

DMWS2016 - 01 - security.pdf	[ ]	1776 Kb
DMWS2016 - 02 - archive.pdf	[ ]	1315 Kb

Course Overview: The goal of the H3ABioNet Data Management workshop is to prepare H3Africa researchers for management of their data, including knowing what data to collect, what file formats, etc. to use. The course will present options for setting up and storing patient data, discuss the EGA requirements to ensure the researchers collect all the necessary data, and determine the computational needs for storing, processing and mining of the data.

Keywords: Data handling, Genomics, Genetics, Biological data resources, Protein analysis, Sequence analysis, Systems Biology, Structure Analysis

Language: English

Skill level: Advanced

Type of training: face-to-face /  in person

Credential awarded: none

Proposed workshop outcomes: The outcome will be that researchers have a better idea of what to expect when their data is generated and how to manage this data effectively.

Proposed workshop relevance: Most of the H3Africa projects are in the stage of data generation and it is important that they know as soon as possible what is involved in data collection and management.

Target audience of the proposed workshop: Data managers from the H3Africa research projects.

Applications are now closed.

Programme: 

1: University of Cape Town, 2: BIKA laboratories, 3: South African National Bioinformatics Institute, 4: Jembi Health Systems, 5: University of the Witwatersrand, 6: European Genome-phenome Archive, 7: University of Illinois.

Group picture of participants and speakers for the H3ABioNet Data Management 2014 workshop.

Training Materials Availability:

Training materials for this course are available as a single downloadable archive here: https://doi.org/10.25375/uct.19130024. Should you re-use any of these materials, please ensure that both the author/s of the material AND H3ABioNet are clearly credited.