Title |
Successful use of whole genome amplified DNA from multiple source types for high-density Illumina SNP microarrays
|
---|---|
Published in |
BMC Genomics, March 2018
|
DOI | 10.1186/s12864-018-4572-6 |
Pubmed ID | |
Authors |
Casey L. Dagnall, Lindsay M. Morton, Belynda D. Hicks, Shengchao Li, Weiyin Zhou, Eric Karlins, Kedest Teshome, Salma Chowdhury, Kerrie S. Lashley, Joshua N. Sampson, Leslie L. Robison, Gregory T. Armstrong, Smita Bhatia, Gretchen A. Radloff, Stella M. Davies, Margaret A. Tucker, Meredith Yeager, Stephen J. Chanock |
Abstract |
The recommended genomic DNA input requirements for whole genome single nucleotide polymorphism microarrays can limit the scope of molecular epidemiological studies. We performed a large-scale evaluation of whole genome amplified DNA as input into high-density, whole-genome Illumina® Infinium® SNP microarray. Overall, 6622 DNA samples from 5970 individuals were obtained from three distinct biospecimen sources and genotyped using gDNA and/or wgaDNA inputs. When genotypes from the same individual were compared with standard, native gDNA input amount, we observed 99.94% mean concordance with wgaDNA input. Our results demonstrate that carefully conducted studies with wgaDNA inputs can yield high-quality genotyping results. These findings should enable investigators to consider expansion of ongoing studies using high-density SNP microarrays, currently challenged by small amounts of available DNA. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 3 | 11% |
Other | 3 | 11% |
Researcher | 3 | 11% |
Student > Ph. D. Student | 3 | 11% |
Professor | 2 | 7% |
Other | 5 | 18% |
Unknown | 9 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 11 | 39% |
Agricultural and Biological Sciences | 4 | 14% |
Medicine and Dentistry | 3 | 11% |
Sports and Recreations | 1 | 4% |
Energy | 1 | 4% |
Other | 1 | 4% |
Unknown | 7 | 25% |