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Probabilistic alignment leads to improved accuracy and read coverage for bisulfite sequencing data

Overview of attention for article published in BMC Bioinformatics, November 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
7 tweeters
googleplus
1 Google+ user

Citations

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7 Dimensions

Readers on

mendeley
44 Mendeley
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Title
Probabilistic alignment leads to improved accuracy and read coverage for bisulfite sequencing data
Published in
BMC Bioinformatics, November 2013
DOI 10.1186/1471-2105-14-337
Pubmed ID
Authors

Changjin Hong, Nathan L Clement, Spencer Clement, Saher Sue Hammoud, Douglas T Carrell, Bradley R Cairns, Quinn Snell, Mark J Clement, William Evan Johnson

Abstract

DNA methylation has been linked to many important biological phenomena. Researchers have recently begun to sequence bisulfite treated DNA to determine its pattern of methylation. However, sequencing reads from bisulfite-converted DNA can vary significantly from the reference genome because of incomplete bisulfite conversion, genome variation, sequencing errors, and poor quality bases. Therefore, it is often difficult to align reads to the correct locations in the reference genome. Furthermore, bisulfite sequencing experiments have the additional complexity of having to estimate the DNA methylation levels within the sample.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 2%
Denmark 1 2%
France 1 2%
Canada 1 2%
Unknown 40 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 48%
Student > Bachelor 5 11%
Other 4 9%
Student > Ph. D. Student 4 9%
Student > Master 3 7%
Other 4 9%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 48%
Biochemistry, Genetics and Molecular Biology 9 20%
Computer Science 4 9%
Engineering 2 5%
Immunology and Microbiology 1 2%
Other 2 5%
Unknown 5 11%

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 13 December 2013.
All research outputs
#4,467,597
of 16,750,089 outputs
Outputs from BMC Bioinformatics
#1,827
of 6,001 outputs
Outputs of similar age
#63,657
of 266,536 outputs
Outputs of similar age from BMC Bioinformatics
#137
of 424 outputs
Altmetric has tracked 16,750,089 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 6,001 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 68% 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 266,536 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 75% of its contemporaries.
We're also able to compare this research output to 424 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 66% of its contemporaries.