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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SAMQA: error classification and validation of high-throughput sequenced read data
|
|---|---|
| Published in |
BMC Genomics, August 2011
|
| DOI | 10.1186/1471-2164-12-419 |
| Pubmed ID | |
| Authors |
Thomas Robinson, Sarah Killcoyne, Ryan Bressler, John Boyle |
| Abstract |
The advances in high-throughput sequencing technologies and growth in data sizes has highlighted the need for scalable tools to perform quality assurance testing. These tests are necessary to ensure that data is of a minimum necessary standard for use in downstream analysis. In this paper we present the SAMQA tool to rapidly and robustly identify errors in population-scale sequence data. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| United Kingdom | 2 | 3% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Germany | 1 | 1% |
| Sweden | 1 | 1% |
| Spain | 1 | 1% |
| Mexico | 1 | 1% |
| Unknown | 58 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 33 | 48% |
| Student > Ph. D. Student | 6 | 9% |
| Professor | 5 | 7% |
| Student > Bachelor | 5 | 7% |
| Professor > Associate Professor | 4 | 6% |
| Other | 10 | 14% |
| Unknown | 6 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 34 | 49% |
| Computer Science | 13 | 19% |
| Engineering | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Social Sciences | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 9 | 13% |
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 22 August 2011.
All research outputs
#18,293,967
of 22,649,029 outputs
Outputs from BMC Genomics
#8,136
of 10,605 outputs
Outputs of similar age
#101,625
of 123,300 outputs
Outputs of similar age from BMC Genomics
#54
of 76 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,605 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 123,300 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.