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BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference

Overview of attention for article published in Genome Biology, September 2018
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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 (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
23 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
42 Dimensions

Readers on

mendeley
66 Mendeley
citeulike
1 CiteULike
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Title
BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference
Published in
Genome Biology, September 2018
DOI 10.1186/s13059-018-1513-2
Pubmed ID
Authors

Elior Rahmani, Regev Schweiger, Liat Shenhav, Theodora Wingert, Ira Hofer, Eilon Gabel, Eleazar Eskin, Eran Halperin

Abstract

We introduce a Bayesian semi-supervised method for estimating cell counts from DNA methylation by leveraging an easily obtainable prior knowledge on the cell-type composition distribution of the studied tissue. We show mathematically and empirically that alternative methods which attempt to infer cell counts without methylation reference only capture linear combinations of cell counts rather than provide one component per cell type. Our approach allows the construction of components such that each component corresponds to a single cell type, and provides a new opportunity to investigate cell compositions in genomic studies of tissues for which it was not possible before.

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 18%
Researcher 12 18%
Student > Master 6 9%
Professor 3 5%
Other 3 5%
Other 7 11%
Unknown 23 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 24%
Agricultural and Biological Sciences 10 15%
Computer Science 7 11%
Business, Management and Accounting 1 2%
Nursing and Health Professions 1 2%
Other 5 8%
Unknown 26 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 13 March 2021.
All research outputs
#2,290,556
of 25,593,129 outputs
Outputs from Genome Biology
#1,884
of 4,492 outputs
Outputs of similar age
#46,249
of 352,290 outputs
Outputs of similar age from Genome Biology
#50
of 80 outputs
Altmetric has tracked 25,593,129 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,492 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 gotten more attention than average, scoring higher than 58% 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 352,290 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 86% of its contemporaries.
We're also able to compare this research output to 80 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.