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ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

Overview of attention for article published in Genome Research, September 2012
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Citations

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1689 Dimensions

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3292 Mendeley
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23 CiteULike
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Title
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia
Published in
Genome Research, September 2012
DOI 10.1101/gr.136184.111
Pubmed ID
Authors

Stephen G. Landt, Georgi K. Marinov, Anshul Kundaje, Pouya Kheradpour, Florencia Pauli, Serafim Batzoglou, Bradley E. Bernstein, Peter Bickel, James B. Brown, Philip Cayting, Yiwen Chen, Gilberto DeSalvo, Charles Epstein, Katherine I. Fisher-Aylor, Ghia Euskirchen, Mark Gerstein, Jason Gertz, Alexander J. Hartemink, Michael M. Hoffman, Vishwanath R. Iyer, Youngsook L. Jung, Subhradip Karmakar, Manolis Kellis, Peter V. Kharchenko, Qunhua Li, Tao Liu, X. Shirley Liu, Lijia Ma, Aleksandar Milosavljevic, Richard M. Myers, Peter J. Park, Michael J. Pazin, Marc D. Perry, Debasish Raha, Timothy E. Reddy, Joel Rozowsky, Noam Shoresh, Arend Sidow, Matthew Slattery, John A. Stamatoyannopoulos, Michael Y. Tolstorukov, Kevin P. White, Simon Xi, Peggy J. Farnham, Jason D. Lieb, Barbara J. Wold, Michael Snyder

Abstract

Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3,292 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 74 2%
United Kingdom 23 <1%
Germany 17 <1%
France 12 <1%
Spain 10 <1%
Italy 9 <1%
Netherlands 7 <1%
China 6 <1%
Mexico 5 <1%
Other 51 2%
Unknown 3078 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 895 27%
Researcher 792 24%
Student > Master 363 11%
Student > Bachelor 252 8%
Student > Doctoral Student 137 4%
Other 473 14%
Unknown 380 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 1407 43%
Biochemistry, Genetics and Molecular Biology 897 27%
Medicine and Dentistry 154 5%
Computer Science 145 4%
Neuroscience 55 2%
Other 200 6%
Unknown 434 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 58. 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 21 March 2024.
All research outputs
#746,397
of 25,837,817 outputs
Outputs from Genome Research
#243
of 4,469 outputs
Outputs of similar age
#3,945
of 189,385 outputs
Outputs of similar age from Genome Research
#8
of 75 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,469 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.9. This one has done particularly well, scoring higher than 94% 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 189,385 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 97% of its contemporaries.
We're also able to compare this research output to 75 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.