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Integrating dilution-based sequencing and population genotypes for single individual haplotyping

Overview of attention for article published in BMC Genomics, January 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

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5 tweeters

Readers on

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9 Mendeley
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Title
Integrating dilution-based sequencing and population genotypes for single individual haplotyping
Published in
BMC Genomics, January 2014
DOI 10.1186/1471-2164-15-733
Pubmed ID
Authors

Hirotaka Matsumoto, Hisanori Kiryu

Abstract

Haplotype information is useful for many genetic analyses and haplotypes are usually inferred using computational approaches. Among such approaches, the importance of single individual haplotyping (SIH), which infers individual haplotypes from sequence fragments, has been increasing with the advent of novel sequencing techniques, such as dilution-based sequencing. These techniques could produce virtual long read fragments by separating DNA fragments into multiple low-concentration aliquots, sequencing and mapping each aliquot, and merging clustered short reads. Although these experimental techniques are sophisticated, they have the problem of producing chimeric fragments whose left and right parts match different chromosomes. In our previous research, we found that chimeric fragments significantly decrease the accuracy of SIH. Although chimeric fragments can be removed by using haplotypes which are determined from pedigree genotypes, pedigree genotypes are generally not available. The length of reads cluster and heterozygous calls were also used to detect chimeric fragments. Although some chimeric fragments will be removed with these features, considerable number of chimeric fragments will be undetected because of the dispersion of the length and the absence of SNPs in the overlapped regions. For these reasons, a general method to detect and remove chimeric fragments is needed.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 33%
Student > Bachelor 2 22%
Researcher 2 22%
Student > Master 1 11%
Professor 1 11%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 44%
Biochemistry, Genetics and Molecular Biology 3 33%
Computer Science 2 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 30 August 2014.
All research outputs
#5,763,720
of 11,275,700 outputs
Outputs from BMC Genomics
#2,829
of 6,783 outputs
Outputs of similar age
#65,658
of 193,873 outputs
Outputs of similar age from BMC Genomics
#79
of 252 outputs
Altmetric has tracked 11,275,700 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,783 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 57% 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 193,873 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 252 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.