| Title |
Recommendations for performance optimizations when using GATK3.8 and GATK4
|
|---|---|
| Published in |
BMC Bioinformatics, November 2019
|
| DOI | 10.1186/s12859-019-3169-7 |
| Pubmed ID | |
| Authors |
Jacob R Heldenbrand, Saurabh Baheti, Matthew A Bockol, Travis M Drucker, Steven N Hart, Matthew E Hudson, Ravishankar K Iyer, Michael T Kalmbach, Katherine I Kendig, Eric W Klee, Nathan R Mattson, Eric D Wieben, Mathieu Wiepert, Derek E Wildman, Liudmila S Mainzer |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 29% |
| United Kingdom | 2 | 29% |
| United States | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 57% |
| Members of the public | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 67 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 24% |
| Student > Ph. D. Student | 11 | 16% |
| Other | 5 | 7% |
| Student > Master | 4 | 6% |
| Student > Postgraduate | 3 | 4% |
| Other | 9 | 13% |
| Unknown | 19 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 37% |
| Agricultural and Biological Sciences | 10 | 15% |
| Computer Science | 6 | 9% |
| Immunology and Microbiology | 2 | 3% |
| Engineering | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 18 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 14 November 2019.
All research outputs
#8,101,899
of 25,736,439 outputs
Outputs from BMC Bioinformatics
#2,910
of 7,739 outputs
Outputs of similar age
#141,635
of 383,157 outputs
Outputs of similar age from BMC Bioinformatics
#72
of 171 outputs
Altmetric has tracked 25,736,439 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,739 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 60% 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 383,157 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 171 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.