Title |
Co-barcoded sequence reads from long DNA fragments: a cost-effective solution for “perfect genome” sequencing
|
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Published in |
Frontiers in Genetics, January 2015
|
DOI | 10.3389/fgene.2014.00466 |
Pubmed ID | |
Authors |
Brock A. Peters, Jia Liu, Radoje Drmanac |
Abstract |
Next generation sequencing (NGS) technologies, primarily based on massively parallel sequencing, have touched and radically changed almost all aspects of research worldwide. These technologies have allowed for the rapid analysis, to date, of the genomes of more than 2,000 different species. In humans, NGS has arguably had the largest impact. Over 100,000 genomes of individual humans (based on various estimates) have been sequenced allowing for deep insights into what makes individuals and families unique and what causes disease in each of us. Despite all of this progress, the current state of the art in sequence technology is far from generating a "perfect genome" sequence and much remains to be understood in the biology of human and other organisms' genomes. In the article that follows, we outline why the "perfect genome" in humans is important, what is lacking from current human whole genome sequences, and a potential strategy for achieving the "perfect genome" in a cost effective manner. |
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Geographical breakdown
Country | Count | As % |
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United States | 4 | 22% |
India | 3 | 17% |
United Kingdom | 2 | 11% |
Norway | 1 | 6% |
China | 1 | 6% |
Sweden | 1 | 6% |
Canada | 1 | 6% |
Australia | 1 | 6% |
Germany | 1 | 6% |
Other | 1 | 6% |
Unknown | 2 | 11% |
Demographic breakdown
Type | Count | As % |
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Scientists | 12 | 67% |
Members of the public | 6 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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France | 2 | 3% |
Japan | 1 | 2% |
United Kingdom | 1 | 2% |
Unknown | 57 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 15 | 25% |
Student > Ph. D. Student | 14 | 23% |
Student > Bachelor | 6 | 10% |
Student > Master | 5 | 8% |
Other | 3 | 5% |
Other | 7 | 11% |
Unknown | 11 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 28% |
Biochemistry, Genetics and Molecular Biology | 14 | 23% |
Computer Science | 5 | 8% |
Medicine and Dentistry | 2 | 3% |
Engineering | 2 | 3% |
Other | 4 | 7% |
Unknown | 17 | 28% |