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Mendeley readers
Attention Score in Context
| Title |
A framework for analyzing DNA methylation data from Illumina Infinium HumanMethylation450 BeadChip
|
|---|---|
| Published in |
BMC Bioinformatics, April 2018
|
| DOI | 10.1186/s12859-018-2096-3 |
| Pubmed ID | |
| Authors |
Zhenxing Wang, XiaoLiang Wu, Yadong Wang |
| Abstract |
DNA methylation has been identified to be widely associated to complex diseases. Among biological platforms to profile DNA methylation in human, the Illumina Infinium HumanMethylation450 BeadChip (450K) has been accepted as one of the most efficient technologies. However, challenges exist in analysis of DNA methylation data generated by this technology due to widespread biases. Here we proposed a generalized framework for evaluating data analysis methods for Illumina 450K array. This framework considers the following steps towards a successful analysis: importing data, quality control, within-array normalization, correcting type bias, detecting differentially methylated probes or regions and biological interpretation. We evaluated five methods using three real datasets, and proposed outperform methods for the Illumina 450K array data analysis. Minfi and methylumi are optimal choice when analyzing small dataset. BMIQ and RCP are proper to correcting type bias and the normalized result of them can be used to discover DMPs. R package missMethyl is suitable for GO term enrichment analysis and biological interpretation. |
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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 140 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 19% |
| Researcher | 24 | 17% |
| Student > Bachelor | 14 | 10% |
| Student > Master | 14 | 10% |
| Student > Doctoral Student | 6 | 4% |
| Other | 10 | 7% |
| Unknown | 46 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 45 | 32% |
| Medicine and Dentistry | 9 | 6% |
| Agricultural and Biological Sciences | 8 | 6% |
| Computer Science | 7 | 5% |
| Engineering | 4 | 3% |
| Other | 12 | 9% |
| Unknown | 55 | 39% |
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 12 April 2018.
All research outputs
#20,480,611
of 23,041,514 outputs
Outputs from BMC Bioinformatics
#6,893
of 7,318 outputs
Outputs of similar age
#290,344
of 329,169 outputs
Outputs of similar age from BMC Bioinformatics
#90
of 106 outputs
Altmetric has tracked 23,041,514 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 7,318 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 1st percentile – i.e., 1% 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 329,169 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 106 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.