Title |
A SNP profiling panel for sample tracking in whole-exome sequencing studies
|
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Published in |
Genome Medicine, September 2013
|
DOI | 10.1186/gm492 |
Pubmed ID | |
Authors |
Reuben J Pengelly, Jane Gibson, Gaia Andreoletti, Andrew Collins, Christopher J Mattocks, Sarah Ennis |
Abstract |
Whole-exome sequencing provides a cost-effective means to sequence protein coding regions within the genome, which are significantly enriched for etiological variants. We describe a panel of single nucleotide polymorphisms (SNPs) to facilitate the validation of data provenance in whole-exome sequencing studies. This is particularly significant where multiple processing steps necessitate transfer of sample custody between clinical, laboratory and bioinformatics facilities. SNPs captured by all commonly used exome enrichment kits were identified, and filtered for possible confounding properties. The optimised panel provides a simple, yet powerful, method for the assignment of intrinsic, highly discriminatory identifiers to genetic samples. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 21% |
United States | 3 | 21% |
Turkey | 1 | 7% |
Germany | 1 | 7% |
Unknown | 6 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 57% |
Scientists | 5 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 3% |
United Kingdom | 2 | 2% |
Italy | 1 | <1% |
Germany | 1 | <1% |
France | 1 | <1% |
Luxembourg | 1 | <1% |
Unknown | 114 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 41 | 33% |
Student > Ph. D. Student | 16 | 13% |
Other | 13 | 10% |
Student > Master | 11 | 9% |
Student > Bachelor | 8 | 6% |
Other | 17 | 14% |
Unknown | 18 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 46 | 37% |
Biochemistry, Genetics and Molecular Biology | 28 | 23% |
Medicine and Dentistry | 17 | 14% |
Computer Science | 3 | 2% |
Engineering | 3 | 2% |
Other | 6 | 5% |
Unknown | 21 | 17% |