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Harmonizing the interpretation of genetic variants across the world: the Malaysian experience

Overview of attention for article published in BMC Research Notes, February 2016
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Title
Harmonizing the interpretation of genetic variants across the world: the Malaysian experience
Published in
BMC Research Notes, February 2016
DOI 10.1186/s13104-015-1798-0
Pubmed ID
Authors

Nik Norliza Nik Hassan, John-Paul Plazzer, Timothy D. Smith, Hashim Halim-Fikri, Finlay Macrae, A. Zubaidi AL, Bin Alwi Zilfalil, Members of Malaysian Node of HVP

Abstract

Databases for gene variants are very useful for sharing genetic data and to facilitate the understanding of the genetic basis of diseases. This report summarises the issues surrounding the development of the Malaysian Human Variome Project Country Node. The focus is on human germline variants. Somatic variants, mitochondrial variants and other types of genetic variation have corresponding databases which are not covered here, as they have specific issues that do not necessarily apply to germline variations. The ethical, legal, social issues, intellectual property, ownership of the data, information technology implementation, and efforts to improve the standards and systems used in data sharing are discussed. An overarching framework such as provided by the Human Variome Project to co-ordinate activities is invaluable. Country Nodes, such as MyHVP, enable human gene variation associated with human diseases to be collected, stored and shared by all disciplines (clinicians, molecular biologists, pathologists, bioinformaticians) for a consistent interpretation of genetic variants locally and across the world.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 2 17%
Lecturer 1 8%
Other 1 8%
Student > Doctoral Student 1 8%
Student > Ph. D. Student 1 8%
Other 2 17%
Unknown 4 33%
Readers by discipline Count As %
Medicine and Dentistry 2 17%
Biochemistry, Genetics and Molecular Biology 1 8%
Linguistics 1 8%
Computer Science 1 8%
Agricultural and Biological Sciences 1 8%
Other 2 17%
Unknown 4 33%