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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Validation and assessment of variant calling pipelines for next-generation sequencing
|
|---|---|
| Published in |
Human Genomics, July 2014
|
| DOI | 10.1186/1479-7364-8-14 |
| Pubmed ID | |
| Authors |
Mehdi Pirooznia, Melissa Kramer, Jennifer Parla, Fernando S Goes, James B Potash, W Richard McCombie, Peter P Zandi |
| Abstract |
The processing and analysis of the large scale data generated by next-generation sequencing (NGS) experiments is challenging and is a burgeoning area of new methods development. Several new bioinformatics tools have been developed for calling sequence variants from NGS data. Here, we validate the variant calling of these tools and compare their relative accuracy to determine which data processing pipeline is optimal. |
X Demographics
The data shown below were collected from the profiles of 21 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 States | 3 | 14% |
| United Kingdom | 3 | 14% |
| Spain | 2 | 10% |
| Switzerland | 2 | 10% |
| Italy | 1 | 5% |
| Finland | 1 | 5% |
| Norway | 1 | 5% |
| Australia | 1 | 5% |
| Mexico | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 5 | 24% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 13 | 62% |
| Members of the public | 8 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 443 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 2% |
| Germany | 4 | <1% |
| United Kingdom | 3 | <1% |
| Netherlands | 2 | <1% |
| Italy | 2 | <1% |
| Norway | 2 | <1% |
| Colombia | 1 | <1% |
| Canada | 1 | <1% |
| Nigeria | 1 | <1% |
| Other | 3 | <1% |
| Unknown | 417 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 110 | 25% |
| Researcher | 100 | 23% |
| Student > Master | 66 | 15% |
| Student > Bachelor | 28 | 6% |
| Other | 25 | 6% |
| Other | 58 | 13% |
| Unknown | 56 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 157 | 35% |
| Biochemistry, Genetics and Molecular Biology | 117 | 26% |
| Medicine and Dentistry | 34 | 8% |
| Computer Science | 33 | 7% |
| Neuroscience | 7 | 2% |
| Other | 27 | 6% |
| Unknown | 68 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 10 June 2015.
All research outputs
#3,202,387
of 25,374,917 outputs
Outputs from Human Genomics
#84
of 564 outputs
Outputs of similar age
#30,795
of 239,660 outputs
Outputs of similar age from Human Genomics
#1
of 7 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 85% 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 239,660 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them