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Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Overview of attention for article published in BMC Bioinformatics, March 2016
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  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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Title
Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains
Published in
BMC Bioinformatics, March 2016
DOI 10.1186/s12859-016-0991-z
Pubmed ID
Authors

Joshua Starmer, Terry Magnuson

Abstract

Correctly identifying genomic regions enriched with histone modifications and transcription factors is key to understanding their regulatory and developmental roles. Conceptually, these regions are divided into two categories, narrow peaks and broad domains, and different algorithms are used to identify each one. Datasets that span these two categories are often analyzed with a single program for peak calling combined with an ad hoc method for domains. We developed hiddenDomains, which identifies both peaks and domains, and compare it to the leading algorithms using H3K27me3, H3K36me3, GABP, ESR1 and FOXA ChIP-seq datasets. The output from the programs was compared to qPCR-validated enriched and depleted sites, predicted transcription factor binding sites, and highly-transcribed gene bodies. With every method, hiddenDomains, performed as well as, if not better than algorithms dedicated to a specific type of analysis. hiddenDomains performs as well as the best domain and peak calling algorithms, making it ideal for analyzing ChIP-seq datasets, especially those that contain a mixture of peaks and domains.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Sweden 1 1%
Italy 1 1%
Unknown 84 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 25%
Researcher 19 22%
Student > Master 9 10%
Student > Bachelor 6 7%
Student > Doctoral Student 5 6%
Other 12 14%
Unknown 14 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 38%
Agricultural and Biological Sciences 23 26%
Immunology and Microbiology 3 3%
Computer Science 3 3%
Medicine and Dentistry 2 2%
Other 6 7%
Unknown 17 20%
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 06 April 2016.
All research outputs
#6,056,922
of 22,858,915 outputs
Outputs from BMC Bioinformatics
#2,254
of 7,293 outputs
Outputs of similar age
#85,817
of 300,491 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 122 outputs
Altmetric has tracked 22,858,915 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 7,293 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 300,491 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 71% of its contemporaries.
We're also able to compare this research output to 122 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 63% of its contemporaries.