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Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells

Overview of attention for article published in Nature, July 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Citations

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223 Dimensions

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687 Mendeley
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15 CiteULike
Title
Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells
Published in
Nature, July 2012
DOI 10.1038/nature11236
Pubmed ID
Authors

Brock A. Peters, Bahram G. Kermani, Andrew B. Sparks, Oleg Alferov, Peter Hong, Andrei Alexeev, Yuan Jiang, Fredrik Dahl, Y. Tom Tang, Juergen Haas, Kimberly Robasky, Alexander Wait Zaranek, Je-Hyuk Lee, Madeleine Price Ball, Joseph E. Peterson, Helena Perazich, George Yeung, Jia Liu, Linsu Chen, Michael I. Kennemer, Kaliprasad Pothuraju, Karel Konvicka, Mike Tsoupko-Sitnikov, Krishna P. Pant, Jessica C. Ebert, Geoffrey B. Nilsen, Jonathan Baccash, Aaron L. Halpern, George M. Church, Radoje Drmanac

Abstract

Recent advances in whole-genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, long fragment read (LFR) technology, which is similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ∼100 picograms of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants were assembled into long haplotype contigs. Removal of false positive single nucleotide variants not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 megabases. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.

X Demographics

X Demographics

The data shown below were collected from the profiles of 144 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 687 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 38 6%
United Kingdom 6 <1%
Germany 4 <1%
Netherlands 3 <1%
France 3 <1%
Brazil 3 <1%
Japan 3 <1%
Belgium 3 <1%
Korea, Republic of 2 <1%
Other 20 3%
Unknown 602 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 205 30%
Student > Ph. D. Student 167 24%
Professor > Associate Professor 54 8%
Other 51 7%
Student > Master 49 7%
Other 123 18%
Unknown 38 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 357 52%
Biochemistry, Genetics and Molecular Biology 110 16%
Medicine and Dentistry 48 7%
Computer Science 41 6%
Engineering 22 3%
Other 55 8%
Unknown 54 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 203. 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 05 March 2024.
All research outputs
#191,752
of 25,332,933 outputs
Outputs from Nature
#11,554
of 97,325 outputs
Outputs of similar age
#800
of 170,478 outputs
Outputs of similar age from Nature
#99
of 947 outputs
Altmetric has tracked 25,332,933 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 97,325 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.4. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 170,478 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 947 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.