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Attention Score in Context
Title |
Response to: Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies
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Published in |
Genome Biology, January 2017
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DOI | 10.1186/s13059-017-1149-7 |
Pubmed ID | |
Authors |
Kevin McGregor, Aurélie Labbe, Celia M. T. Greenwood |
Abstract |
We thank Hattab and colleagues for their correspondence and their investigation of cell-type mixture correction methods in methyl-CG binding domain sequencing. Here, we speculate on why surrogate variable analysis (SVA) performed differently between their two data sets, and poorly in one of them.Please see related Correspondence article: https://genomebiology.biomedcentral.com/articles/10/1186/s13059-017-1148-8 and related Research article: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0935-y. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 25% |
Student > Ph. D. Student | 2 | 25% |
Student > Bachelor | 1 | 13% |
Student > Master | 1 | 13% |
Professor > Associate Professor | 1 | 13% |
Other | 0 | 0% |
Unknown | 1 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 4 | 50% |
Mathematics | 1 | 13% |
Nursing and Health Professions | 1 | 13% |
Psychology | 1 | 13% |
Unknown | 1 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 31 January 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Genome Biology
#4,395
of 4,468 outputs
Outputs of similar age
#365,083
of 424,069 outputs
Outputs of similar age from Genome Biology
#58
of 61 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.