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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Bioinformatics Pipelines for Targeted Resequencing and Whole-Exome Sequencing of Human and Mouse Genomes: A Virtual Appliance Approach for Instant Deployment
|
|---|---|
| Published in |
PLOS ONE, April 2014
|
| DOI | 10.1371/journal.pone.0095217 |
| Pubmed ID | |
| Authors |
Jason Li, Maria A. Doyle, Isaam Saeed, Stephen Q. Wong, Victoria Mar, David L. Goode, Franco Caramia, Ken Doig, Georgina L. Ryland, Ella R. Thompson, Sally M. Hunter, Saman K. Halgamuge, Jason Ellul, Alexander Dobrovic, Ian G. Campbell, Anthony T. Papenfuss, Grant A. McArthur, Richard W. Tothill |
| Abstract |
Targeted resequencing by massively parallel sequencing has become an effective and affordable way to survey small to large portions of the genome for genetic variation. Despite the rapid development in open source software for analysis of such data, the practical implementation of these tools through construction of sequencing analysis pipelines still remains a challenging and laborious activity, and a major hurdle for many small research and clinical laboratories. We developed TREVA (Targeted REsequencing Virtual Appliance), making pre-built pipelines immediately available as a virtual appliance. Based on virtual machine technologies, TREVA is a solution for rapid and efficient deployment of complex bioinformatics pipelines to laboratories of all sizes, enabling reproducible results. The analyses that are supported in TREVA include: somatic and germline single-nucleotide and insertion/deletion variant calling, copy number analysis, and cohort-based analyses such as pathway and significantly mutated genes analyses. TREVA is flexible and easy to use, and can be customised by Linux-based extensions if required. TREVA can also be deployed on the cloud (cloud computing), enabling instant access without investment overheads for additional hardware. TREVA is available at http://bioinformatics.petermac.org/treva/. |
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 % |
|---|---|---|
| United Kingdom | 1 | 14% |
| France | 1 | 14% |
| United States | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 4% |
| United Kingdom | 3 | 3% |
| Italy | 1 | <1% |
| Brazil | 1 | <1% |
| Sweden | 1 | <1% |
| Germany | 1 | <1% |
| Netherlands | 1 | <1% |
| Czechia | 1 | <1% |
| China | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 104 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 41 | 34% |
| Student > Master | 17 | 14% |
| Student > Ph. D. Student | 16 | 13% |
| Other | 14 | 12% |
| Student > Bachelor | 8 | 7% |
| Other | 17 | 14% |
| Unknown | 7 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 38 | 32% |
| Biochemistry, Genetics and Molecular Biology | 27 | 23% |
| Computer Science | 18 | 15% |
| Medicine and Dentistry | 13 | 11% |
| Engineering | 3 | 3% |
| Other | 9 | 8% |
| Unknown | 12 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 27 February 2015.
All research outputs
#6,271,351
of 22,754,104 outputs
Outputs from PLOS ONE
#75,166
of 194,175 outputs
Outputs of similar age
#60,066
of 226,772 outputs
Outputs of similar age from PLOS ONE
#1,607
of 4,952 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 194,175 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. 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 226,772 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 73% of its contemporaries.
We're also able to compare this research output to 4,952 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 66% of its contemporaries.