↓ Skip to main content

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

Overview of attention for article published in BMC Genomics, November 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
13 tweeters

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
68 Mendeley
citeulike
2 CiteULike
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
The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data
Published in
BMC Genomics, November 2016
DOI 10.1186/s12864-016-3288-8
Pubmed ID
Authors

Giovanna Ambrosini, René Dreos, Sunil Kumar, Philipp Bucher

Abstract

ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data. Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade. The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/ .

Twitter Demographics

The data shown below were collected from the profiles of 13 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 1%
France 1 1%
Unknown 66 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 24%
Student > Master 14 21%
Researcher 12 18%
Student > Bachelor 9 13%
Student > Doctoral Student 4 6%
Other 6 9%
Unknown 7 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 37%
Agricultural and Biological Sciences 17 25%
Computer Science 8 12%
Medicine and Dentistry 3 4%
Chemistry 2 3%
Other 4 6%
Unknown 9 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 30 November 2016.
All research outputs
#2,601,640
of 16,519,376 outputs
Outputs from BMC Genomics
#1,184
of 9,065 outputs
Outputs of similar age
#74,640
of 393,827 outputs
Outputs of similar age from BMC Genomics
#127
of 873 outputs
Altmetric has tracked 16,519,376 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,065 research outputs from this source. They receive a mean Attention Score of 4.3. 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 393,827 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 81% of its contemporaries.
We're also able to compare this research output to 873 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.