↓ Skip to main content

Model-based Analysis of ChIP-Seq (MACS)

Overview of attention for article published in Genome Biology (Online Edition), September 2008
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

news
2 news outlets
blogs
2 blogs
twitter
1 tweeter
patent
40 patents
wikipedia
6 Wikipedia pages
q&a
1 Q&A thread

Citations

dimensions_citation
10740 Dimensions

Readers on

mendeley
5372 Mendeley
citeulike
69 CiteULike
connotea
11 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Model-based Analysis of ChIP-Seq (MACS)
Published in
Genome Biology (Online Edition), September 2008
DOI 10.1186/gb-2008-9-9-r137
Pubmed ID
Authors

Yong Zhang, Tao Liu, Clifford A Meyer, Jérôme Eeckhoute, David S Johnson, Bradley E Bernstein, Chad Nusbaum, Richard M Myers, Myles Brown, Wei Li, X Shirley Liu

Abstract

We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 5,372 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 107 2%
United Kingdom 36 <1%
Germany 25 <1%
France 13 <1%
Italy 12 <1%
Spain 9 <1%
China 9 <1%
Netherlands 8 <1%
Brazil 8 <1%
Other 61 1%
Unknown 5084 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1619 30%
Researcher 1094 20%
Student > Master 550 10%
Student > Bachelor 434 8%
Student > Doctoral Student 285 5%
Other 688 13%
Unknown 702 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 1999 37%
Biochemistry, Genetics and Molecular Biology 1657 31%
Medicine and Dentistry 227 4%
Computer Science 194 4%
Neuroscience 111 2%
Other 377 7%
Unknown 807 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 48. 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 26 October 2022.
All research outputs
#732,130
of 22,557,175 outputs
Outputs from Genome Biology (Online Edition)
#546
of 4,088 outputs
Outputs of similar age
#1,365
of 73,663 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 5 outputs
Altmetric has tracked 22,557,175 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,088 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 86% 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 73,663 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them