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ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis

Overview of attention for article published in BMC Genomics, February 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)

Mentioned by

twitter
3 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
112 Dimensions

Readers on

mendeley
456 Mendeley
citeulike
11 CiteULike
connotea
1 Connotea
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Title
ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis
Published in
BMC Genomics, February 2011
DOI 10.1186/1471-2164-12-134
Pubmed ID
Authors

Joshua WK Ho, Eric Bishop, Peter V Karchenko, Nicolas Nègre, Kevin P White, Peter J Park

Abstract

Chromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of Drosophila melanogaster.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 456 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 21 5%
United Kingdom 8 2%
France 6 1%
Germany 4 <1%
Switzerland 4 <1%
Spain 3 <1%
Italy 3 <1%
Netherlands 2 <1%
China 2 <1%
Other 12 3%
Unknown 391 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 138 30%
Researcher 116 25%
Student > Master 55 12%
Student > Bachelor 36 8%
Professor > Associate Professor 20 4%
Other 62 14%
Unknown 29 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 249 55%
Biochemistry, Genetics and Molecular Biology 94 21%
Computer Science 23 5%
Medicine and Dentistry 15 3%
Engineering 8 2%
Other 33 7%
Unknown 34 7%

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 18 December 2020.
All research outputs
#4,584,299
of 17,351,915 outputs
Outputs from BMC Genomics
#2,107
of 9,280 outputs
Outputs of similar age
#28,137
of 101,384 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
Altmetric has tracked 17,351,915 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 9,280 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 76% 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 101,384 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 72% of its contemporaries.
We're also able to compare this research output to 1 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