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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Estimation of CpG coverage in whole methylome next-generation sequencing studies
|
|---|---|
| Published in |
BMC Bioinformatics, February 2013
|
| DOI | 10.1186/1471-2105-14-50 |
| Pubmed ID | |
| Authors |
Edwin JCG van den Oord, Jozsef Bukszar, Gábor Rudolf, Srilaxmi Nerella, Joseph L McClay, Lin Y Xie, Karolina A Aberg |
| Abstract |
Methylation studies are a promising complement to genetic studies of DNA sequence. However, detailed prior biological knowledge is typically lacking, so methylome-wide association studies (MWAS) will be critical to detect disease relevant sites. A cost-effective approach involves the next-generation sequencing (NGS) of single-end libraries created from samples that are enriched for methylated DNA fragments. A limitation of single-end libraries is that the fragment size distribution is not observed. This hampers several aspects of the data analysis such as the calculation of enrichment measures that are based on the number of fragments covering the CpGs. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 5% |
| Japan | 1 | 2% |
| Luxembourg | 1 | 2% |
| Belgium | 1 | 2% |
| Unknown | 49 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 28 | 51% |
| Student > Ph. D. Student | 7 | 13% |
| Professor > Associate Professor | 5 | 9% |
| Professor | 3 | 5% |
| Other | 3 | 5% |
| Other | 6 | 11% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 44% |
| Biochemistry, Genetics and Molecular Biology | 10 | 18% |
| Medicine and Dentistry | 4 | 7% |
| Mathematics | 3 | 5% |
| Computer Science | 2 | 4% |
| Other | 4 | 7% |
| Unknown | 8 | 15% |
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 18 February 2013.
All research outputs
#15,263,666
of 22,696,971 outputs
Outputs from BMC Bioinformatics
#5,362
of 7,254 outputs
Outputs of similar age
#185,178
of 287,465 outputs
Outputs of similar age from BMC Bioinformatics
#103
of 141 outputs
Altmetric has tracked 22,696,971 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 287,465 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.