| Title |
Pisces: an accurate and versatile variant caller for somatic and germline next-generation sequencing data
|
|---|---|
| Published in |
Bioinformatics, October 2018
|
| DOI | 10.1093/bioinformatics/bty849 |
| Pubmed ID | |
| Authors |
Tamsen Dunn, Gwenn Berry, Dorothea Emig-Agius, Yu Jiang, Serena Lei, Anita Iyer, Nitin Udar, Han-Yu Chuang, Jeff Hegarty, Michael Dickover, Brandy Klotzle, Justin Robbins, Marina Bibikova, Marc Peeters, Michael Strömberg |
X Demographics
The data shown below were collected from the profiles of 4 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 Kingdom | 2 | 50% |
| Argentina | 1 | 25% |
| Spain | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 18% |
| Student > Master | 11 | 14% |
| Student > Ph. D. Student | 9 | 11% |
| Other | 5 | 6% |
| Student > Bachelor | 5 | 6% |
| Other | 6 | 8% |
| Unknown | 29 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 22 | 28% |
| Medicine and Dentistry | 8 | 10% |
| Agricultural and Biological Sciences | 8 | 10% |
| Engineering | 3 | 4% |
| Computer Science | 1 | 1% |
| Other | 5 | 6% |
| Unknown | 32 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 19 May 2019.
All research outputs
#14,429,961
of 23,577,761 outputs
Outputs from Bioinformatics
#6,743
of 9,035 outputs
Outputs of similar age
#187,178
of 347,522 outputs
Outputs of similar age from Bioinformatics
#134
of 206 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,035 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 23rd percentile – i.e., 23% 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 347,522 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 206 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.