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Improving bioinformatic pipelines for exome variant calling

Overview of attention for article published in Genome Medicine, January 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users
patent
2 patents

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
64 Mendeley
citeulike
5 CiteULike
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Title
Improving bioinformatic pipelines for exome variant calling
Published in
Genome Medicine, January 2012
DOI 10.1186/gm306
Pubmed ID
Authors

Hanlee P Ji

Abstract

Exome sequencing analysis is a cost-effective approach for identifying variants in coding regions. However, recognizing the relevant single nucleotide variants, small insertions and deletions remains a challenge for many researchers and diagnostic laboratories typically do not have access to the bioinformatic analysis pipelines necessary for clinical application. The Atlas2 suite, recently released by Baylor Genome Center, is designed to be widely accessible, runs on desktop computers but is scalable to computational clusters, and performs comparably with other popular variant callers. Atlas2 may be an accessible alternative for data processing when a rapid solution for variant calling is required.See research article http://www.biomedcentral.com/1471-2105/13/8.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 9%
United Kingdom 4 6%
Italy 1 2%
Germany 1 2%
Korea, Republic of 1 2%
Kenya 1 2%
Unknown 50 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 39%
Student > Ph. D. Student 9 14%
Student > Master 9 14%
Other 5 8%
Student > Postgraduate 5 8%
Other 10 16%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 52%
Biochemistry, Genetics and Molecular Biology 12 19%
Computer Science 5 8%
Medicine and Dentistry 5 8%
Engineering 2 3%
Other 3 5%
Unknown 4 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 24 October 2023.
All research outputs
#7,047,742
of 25,374,647 outputs
Outputs from Genome Medicine
#1,137
of 1,585 outputs
Outputs of similar age
#58,606
of 253,324 outputs
Outputs of similar age from Genome Medicine
#14
of 21 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,585 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 253,324 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.