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| Title |
affy2sv: an R package to pre-process Affymetrix CytoScan HD and 750K arrays for SNP, CNV, inversion and mosaicism calling
|
|---|---|
| Published in |
BMC Bioinformatics, May 2015
|
| DOI | 10.1186/s12859-015-0608-y |
| Pubmed ID | |
| Authors |
Carles Hernandez-Ferrer, Ines Quintela Garcia, Katharina Danielski, Ángel Carracedo, Luis A. Pérez-Jurado, Juan R. González |
| Abstract |
The well-known Genome-Wide Association Studies (GWAS) had led to many scientific discoveries using SNP data. Even so, they were not able to explain the full heritability of complex diseases. Now, other structural variants like copy number variants or DNA inversions, either germ-line or in mosaicism events, are being studies. We present the R package affy2sv to pre-process Affymetrix CytoScan HD/750k array (also for Genome-Wide SNP 5.0/6.0 and Axiom) in structural variant studies. We illustrate the capabilities of affy2sv using two different complete pipelines on real data. The first one performing a GWAS and a mosaic alterations detection study, and the other detecting CNVs and performing an inversion calling. Both examples presented in the article show up how affy2sv can be used as part of more complex pipelines aimed to analyze Affymetrix SNP arrays data in genetic association studies, where different types of structural variants are considered. |
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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Unknown | 54 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 24% |
| Researcher | 12 | 22% |
| Other | 7 | 13% |
| Student > Master | 5 | 9% |
| Student > Bachelor | 4 | 7% |
| Other | 7 | 13% |
| Unknown | 7 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 35% |
| Agricultural and Biological Sciences | 10 | 18% |
| Medicine and Dentistry | 7 | 13% |
| Computer Science | 4 | 7% |
| Immunology and Microbiology | 3 | 5% |
| Other | 1 | 2% |
| Unknown | 11 | 20% |
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 21 May 2015.
All research outputs
#20,273,512
of 22,805,349 outputs
Outputs from BMC Bioinformatics
#6,853
of 7,281 outputs
Outputs of similar age
#223,232
of 266,611 outputs
Outputs of similar age from BMC Bioinformatics
#112
of 121 outputs
Altmetric has tracked 22,805,349 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 7,281 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.
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We're also able to compare this research output to 121 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.