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Optimizing illumina next-generation sequencing library preparation for extremely at-biased genomes

Overview of attention for article published in BMC Genomics, January 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
1 blog
twitter
7 X users
patent
17 patents

Citations

dimensions_citation
600 Dimensions

Readers on

mendeley
450 Mendeley
citeulike
9 CiteULike
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Title
Optimizing illumina next-generation sequencing library preparation for extremely at-biased genomes
Published in
BMC Genomics, January 2012
DOI 10.1186/1471-2164-13-1
Pubmed ID
Authors

Samuel O Oyola, Thomas D Otto, Yong Gu, Gareth Maslen, Magnus Manske, Susana Campino, Daniel J Turner, Bronwyn MacInnis, Dominic P Kwiatkowski, Harold P Swerdlow, Michael A Quail

Abstract

Massively parallel sequencing technology is revolutionizing approaches to genomic and genetic research. Since its advent, the scale and efficiency of Next-Generation Sequencing (NGS) has rapidly improved. In spite of this success, sequencing genomes or genomic regions with extremely biased base composition is still a great challenge to the currently available NGS platforms. The genomes of some important pathogenic organisms like Plasmodium falciparum (high AT content) and Mycobacterium tuberculosis (high GC content) display extremes of base composition. The standard library preparation procedures that employ PCR amplification have been shown to cause uneven read coverage particularly across AT and GC rich regions, leading to problems in genome assembly and variation analyses. Alternative library-preparation approaches that omit PCR amplification require large quantities of starting material and hence are not suitable for small amounts of DNA/RNA such as those from clinical isolates. We have developed and optimized library-preparation procedures suitable for low quantity starting material and tolerant to extremely high AT content sequences.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 450 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 13 3%
United States 6 1%
Germany 5 1%
Spain 3 <1%
Australia 2 <1%
Korea, Republic of 1 <1%
Brazil 1 <1%
Sweden 1 <1%
Israel 1 <1%
Other 9 2%
Unknown 408 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 128 28%
Student > Ph. D. Student 111 25%
Student > Master 48 11%
Student > Bachelor 30 7%
Other 27 6%
Other 57 13%
Unknown 49 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 227 50%
Biochemistry, Genetics and Molecular Biology 89 20%
Medicine and Dentistry 23 5%
Engineering 8 2%
Immunology and Microbiology 7 2%
Other 36 8%
Unknown 60 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 15 August 2023.
All research outputs
#2,174,759
of 25,374,917 outputs
Outputs from BMC Genomics
#538
of 11,244 outputs
Outputs of similar age
#15,394
of 250,257 outputs
Outputs of similar age from BMC Genomics
#3
of 141 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 95% 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 250,257 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 93% of its contemporaries.
We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.