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Mendeley readers
Attention Score in Context
| Title |
Between-array normalization for 450K data
|
|---|---|
| Published in |
Frontiers in Genetics, March 2015
|
| DOI | 10.3389/fgene.2015.00092 |
| Pubmed ID | |
| Authors |
Jonathan A. Heiss, Hermann Brenner |
| Abstract |
The Illumina Infinium HumanMethylation450 BeadChip is frequently used in epigenetic research. Besides quantile normalization there is currently no standard method to normalize the data between arrays. We describe some properties of the data generated by this platform and present a normalization method based on local regression. We compare the performance of this method with other commonly used approaches in three benchmarks (correlation between 21 pairs of technical replicates, detection of differential methylation and correlation of methylation levels for smoking-associated CpG sites with smoking behavior of 655 participants of an epidemiological study). Results indicate that the proposed method improves reproducibility, whereas some commonly used methods can have adverse effects. |
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 % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Iran, Islamic Republic of | 1 | 2% |
| Turkey | 1 | 2% |
| Unknown | 56 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 27% |
| Researcher | 14 | 23% |
| Student > Master | 11 | 18% |
| Student > Postgraduate | 4 | 7% |
| Other | 2 | 3% |
| Other | 5 | 8% |
| Unknown | 8 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 30% |
| Biochemistry, Genetics and Molecular Biology | 15 | 25% |
| Computer Science | 8 | 13% |
| Medicine and Dentistry | 6 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 9 | 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 26 March 2015.
All research outputs
#17,750,476
of 22,794,367 outputs
Outputs from Frontiers in Genetics
#6,059
of 11,761 outputs
Outputs of similar age
#176,511
of 258,975 outputs
Outputs of similar age from Frontiers in Genetics
#128
of 156 outputs
Altmetric has tracked 22,794,367 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,761 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 40th percentile – i.e., 40% 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 258,975 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.