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BatMeth: improved mapper for bisulfite sequencing reads on DNA methylation

Overview of attention for article published in Genome Biology, October 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)

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Citations

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46 Dimensions

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128 Mendeley
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1 CiteULike
Title
BatMeth: improved mapper for bisulfite sequencing reads on DNA methylation
Published in
Genome Biology, October 2012
DOI 10.1186/gb-2012-13-10-r82
Pubmed ID
Authors

Jing-Quan Lim, Chandana Tennakoon, Guoliang Li, Eleanor Wong, Yijun Ruan, Chia-Lin Wei, Wing-Kin Sung

Abstract

ABSTRACT: DNA methylation plays a crucial role in higher organisms. Coupling bisulfite treatment with next generation sequencing enables the interrogation of 5-methylcytosine sites in the genome. However, bisulfite conversion introduces mismatches between the reads and the reference genome, which makes mapping of Illumina and SOLiD reads slow and inaccurate. BatMeth is an algorithm that integrates novel Mismatch Counting, List Filtering, Mismatch Stage Filtering and Fast Mapping onto Two Indexes components to improve unique mapping rate, speed and precision. Experimental results show that BatMeth is faster and more accurate than existing tools. BatMeth is freely available at http://code.google.com/p/batmeth/.

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 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 5%
United Kingdom 2 2%
India 2 2%
Germany 1 <1%
Sweden 1 <1%
France 1 <1%
Belgium 1 <1%
New Zealand 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 110 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 46 36%
Student > Ph. D. Student 24 19%
Professor 10 8%
Student > Master 9 7%
Professor > Associate Professor 8 6%
Other 20 16%
Unknown 11 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 54%
Biochemistry, Genetics and Molecular Biology 25 20%
Computer Science 10 8%
Medicine and Dentistry 4 3%
Mathematics 2 2%
Other 6 5%
Unknown 12 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 November 2013.
All research outputs
#7,714,565
of 25,374,917 outputs
Outputs from Genome Biology
#3,359
of 4,467 outputs
Outputs of similar age
#57,309
of 191,479 outputs
Outputs of similar age from Genome Biology
#42
of 55 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 24th percentile – i.e., 24% 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 191,479 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 69% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.