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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
|
|---|---|
| Published in |
BMC Bioinformatics, December 2015
|
| DOI | 10.1186/s12859-015-0840-5 |
| Pubmed ID | |
| Authors |
Andy Kilianski, Patrick Carcel, Shijie Yao, Pierce Roth, Josh Schulte, Greg B. Donarum, Ed T. Fochler, Jessica M. Hill, Alvin T. Liem, Michael R. Wiley, Jason T. Ladner, Bradley P. Pfeffer, Oliver Elliot, Alexandra Petrosov, Dereje D. Jima, Tyghe G. Vallard, Melanie C. Melendrez, Evan Skowronski, Phenix-Lan Quan, W. Ian Lipkin, Henry S. Gibbons, David L. Hirschberg, Gustavo F. Palacios, C. Nicole Rosenzweig |
| Abstract |
The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available. |
X Demographics
The data shown below were collected from the profiles of 31 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 | 4 | 13% |
| United States | 4 | 13% |
| Canada | 2 | 6% |
| France | 1 | 3% |
| Belgium | 1 | 3% |
| Spain | 1 | 3% |
| Israel | 1 | 3% |
| Netherlands | 1 | 3% |
| Unknown | 16 | 52% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 20 | 65% |
| Members of the public | 10 | 32% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Ireland | 1 | 1% |
| Sweden | 1 | 1% |
| Brazil | 1 | 1% |
| Egypt | 1 | 1% |
| United Kingdom | 1 | 1% |
| Unknown | 91 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 32% |
| Student > Ph. D. Student | 16 | 16% |
| Student > Master | 15 | 15% |
| Student > Doctoral Student | 5 | 5% |
| Student > Bachelor | 5 | 5% |
| Other | 17 | 17% |
| Unknown | 9 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 39 | 40% |
| Biochemistry, Genetics and Molecular Biology | 15 | 15% |
| Computer Science | 7 | 7% |
| Medicine and Dentistry | 5 | 5% |
| Engineering | 5 | 5% |
| Other | 17 | 17% |
| Unknown | 10 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 20 December 2016.
All research outputs
#1,934,589
of 24,266,964 outputs
Outputs from BMC Bioinformatics
#435
of 7,510 outputs
Outputs of similar age
#33,830
of 401,603 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 142 outputs
Altmetric has tracked 24,266,964 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,510 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 done particularly well, scoring higher than 94% 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 401,603 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.