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Analysis of archived residual newborn screening blood spots after whole genome amplification

Overview of attention for article published in BMC Genomics, August 2015
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Title
Analysis of archived residual newborn screening blood spots after whole genome amplification
Published in
BMC Genomics, August 2015
DOI 10.1186/s12864-015-1747-2
Pubmed ID
Authors

Brandi L. Cantarel, Yunping Lei, Daniel Weaver, Huiping Zhu, Andrew Farrell, Graeme Benstead-Hume, Justin Reese, Richard H. Finnell

Abstract

Deidentified newborn screening bloodspot samples (NBS) represent a valuable potential resource for genomic research if impediments to whole exome sequencing of NBS deoxyribonucleic acid (DNA), including the small amount of genomic DNA in NBS material, can be overcome. For instance, genomic analysis of NBS could be used to define allele frequencies of disease-associated variants in local populations, or to conduct prospective or retrospective studies relating genomic variation to disease emergence in pediatric populations over time. In this study, we compared the recovery of variant calls from exome sequences of amplified NBS genomic DNA to variant calls from exome sequencing of non-amplified NBS DNA from the same individuals. Using a standard alignment-based Genome Analysis Toolkit (GATK), we find 62,000-76,000 additional variants in amplified samples. After application of a unique kmer enumeration and variant detection method (RUFUS), only 38,000-47,000 additional variants are observed in amplified gDNA. This result suggests that roughly half of the amplification-introduced variants identified using GATK may be the result of mapping errors and read misalignment. Our results show that it is possible to obtain informative, high-quality data from exome analysis of whole genome amplified NBS with the important caveat that different data generation and analysis methods can affect variant detection accuracy, and the concordance of variant calls in whole-genome amplified and non-amplified exomes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 19%
Student > Master 3 14%
Researcher 3 14%
Other 2 10%
Student > Postgraduate 2 10%
Other 5 24%
Unknown 2 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 29%
Biochemistry, Genetics and Molecular Biology 5 24%
Medicine and Dentistry 3 14%
Nursing and Health Professions 1 5%
Immunology and Microbiology 1 5%
Other 1 5%
Unknown 4 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 August 2015.
All research outputs
#20,286,650
of 22,821,814 outputs
Outputs from BMC Genomics
#9,280
of 10,654 outputs
Outputs of similar age
#221,486
of 264,395 outputs
Outputs of similar age from BMC Genomics
#239
of 254 outputs
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