Title |
Molecular diagnostics for congenital hearing loss including 15 deafness genes using a next generation sequencing platform
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Published in |
BMC Medical Genomics, May 2012
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DOI | 10.1186/1755-8794-5-17 |
Pubmed ID | |
Authors |
Sarah De Keulenaer, Jan Hellemans, Steve Lefever, Jean-Pierre Renard, Joachim De Schrijver, Hendrik Van de Voorde, Mohammad Amin Tabatabaiefar, Filip Van Nieuwerburgh, Daisy Flamez, Filip Pattyn, Bieke Scharlaken, Dieter Deforce, Sofie Bekaert, Wim Van Criekinge, Jo Vandesompele, Guy Van Camp, Paul Coucke |
Abstract |
Hereditary hearing loss (HL) can originate from mutations in one of many genes involved in the complex process of hearing. Identification of the genetic defects in patients is currently labor intensive and expensive. While screening with Sanger sequencing for GJB2 mutations is common, this is not the case for the other known deafness genes (> 60). Next generation sequencing technology (NGS) has the potential to be much more cost efficient. Published methods mainly use hybridization based target enrichment procedures that are time saving and efficient, but lead to loss in sensitivity. In this study we used a semi-automated PCR amplification and NGS in order to combine high sensitivity, speed and cost efficiency. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Belgium | 1 | 1% |
South Africa | 1 | 1% |
Brazil | 1 | 1% |
Unknown | 74 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 12 | 15% |
Student > Ph. D. Student | 10 | 13% |
Student > Master | 9 | 12% |
Student > Bachelor | 8 | 10% |
Other | 7 | 9% |
Other | 23 | 29% |
Unknown | 9 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 23 | 29% |
Biochemistry, Genetics and Molecular Biology | 19 | 24% |
Medicine and Dentistry | 15 | 19% |
Engineering | 2 | 3% |
Social Sciences | 2 | 3% |
Other | 4 | 5% |
Unknown | 13 | 17% |