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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types
|
|---|---|
| Published in |
Genome Biology, January 2017
|
| DOI | 10.1186/s13059-017-1156-8 |
| Pubmed ID | |
| Authors |
Simone Ecker, Lu Chen, Vera Pancaldi, Frederik O. Bagger, José María Fernández, Enrique Carrillo de Santa Pau, David Juan, Alice L. Mann, Stephen Watt, Francesco Paolo Casale, Nikos Sidiropoulos, Nicolas Rapin, Angelika Merkel, BLUEPRINT Consortium, Hendrik G. Stunnenberg, Oliver Stegle, Mattia Frontini, Kate Downes, Tomi Pastinen, Taco W. Kuijpers, Daniel Rico, Alfonso Valencia, Stephan Beck, Nicole Soranzo, Dirk S. Paul |
| Abstract |
A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. We apply a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14(+)CD16(-) monocytes, CD66b(+)CD16(+) neutrophils, and CD4(+)CD45RA(+) naïve T cells from the same 125 healthy individuals. We discover substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression are found to be implicated in key immune pathways and are associated with cellular properties and environmental exposure. We also observe increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites are enriched at dynamic chromatin regions and active enhancers. Our data highlight the importance of transcriptional and epigenetic variability for the key role of neutrophils as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability . |
X Demographics
The data shown below were collected from the profiles of 45 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 12 | 27% |
| United States | 4 | 9% |
| Spain | 4 | 9% |
| France | 2 | 4% |
| Malaysia | 1 | 2% |
| Estonia | 1 | 2% |
| Germany | 1 | 2% |
| Norway | 1 | 2% |
| Turkey | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 15 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 23 | 51% |
| Members of the public | 21 | 47% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | <1% |
| Denmark | 2 | <1% |
| Sweden | 1 | <1% |
| Canada | 1 | <1% |
| Germany | 1 | <1% |
| Mexico | 1 | <1% |
| Greece | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 235 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 69 | 28% |
| Student > Ph. D. Student | 55 | 22% |
| Student > Master | 19 | 8% |
| Student > Doctoral Student | 14 | 6% |
| Student > Bachelor | 13 | 5% |
| Other | 36 | 15% |
| Unknown | 39 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 71 | 29% |
| Agricultural and Biological Sciences | 60 | 24% |
| Medicine and Dentistry | 21 | 9% |
| Immunology and Microbiology | 21 | 9% |
| Computer Science | 15 | 6% |
| Other | 13 | 5% |
| Unknown | 44 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 November 2019.
All research outputs
#1,593,220
of 25,754,670 outputs
Outputs from Genome Biology
#1,281
of 4,512 outputs
Outputs of similar age
#32,473
of 424,751 outputs
Outputs of similar age from Genome Biology
#20
of 62 outputs
Altmetric has tracked 25,754,670 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,512 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has gotten more attention than average, scoring higher than 71% 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 424,751 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 92% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.