| Title |
WHATIF: An open-source desktop application for extraction and management of the incidental findings from next-generation sequencing variant data
|
|---|---|
| Published in |
Computers in Biology & Medicine, April 2015
|
| DOI | 10.1016/j.compbiomed.2015.03.028 |
| Pubmed ID | |
| Authors |
Zhan Ye, Christopher Kadolph, Robert Strenn, Daniel Wall, Elizabeth McPherson, Simon Lin |
| Abstract |
Identification and evaluation of incidental findings in patients following whole exome (WGS) or whole genome sequencing (WGS) is challenging for both practicing physicians and researchers. The American College of Medical Genetics and Genomics (ACMG) recently recommended a list of reportable incidental genetic findings. However, no informatics tools are currently available to support evaluation of incidental findings in next-generation sequencing data. The Wisconsin Hierarchical Analysis Tool for Incidental Findings (WHATIF), was developed as a stand-alone Windows-based desktop executable, to support the interactive analysis of incidental findings in the context of the ACMG recommendations. WHATIF integrates the European Bioinformatics Institute Variant Effect Predictor (VEP) tool for biological interpretation and the National Center for Biotechnology Information ClinVar tool for clinical interpretation. An open-source desktop program was created to annotate incidental findings and present the results with a user-friendly interface. Further, a meaningful index (WHATIF Index) was devised for each gene to facilitate ranking of the relative importance of the variants and estimate the potential workload associated with further evaluation of the variants. Our WHATIF application is available at: http://tinyurl.com/WHATIF-SOFTWARE CONCLUSIONS: The WHATIF application offers a user-friendly interface and allows users to investigate the extracted variant information efficiently and intuitively while always accessing the up to date information on variants via application programming interfaces (API) connections. WHATIF׳s highly flexible design and straightforward implementation aids users in customizing the source code to meet their own special needs. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| France | 1 | 3% |
| Italy | 1 | 3% |
| Unknown | 28 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 32% |
| Researcher | 6 | 19% |
| Student > Bachelor | 4 | 13% |
| Student > Master | 4 | 13% |
| Other | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 2 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 35% |
| Computer Science | 4 | 13% |
| Engineering | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Social Sciences | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 5 | 16% |
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 24 April 2015.
All research outputs
#16,821,176
of 25,707,225 outputs
Outputs from Computers in Biology & Medicine
#1,419
of 2,818 outputs
Outputs of similar age
#160,596
of 280,727 outputs
Outputs of similar age from Computers in Biology & Medicine
#11
of 28 outputs
Altmetric has tracked 25,707,225 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,818 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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We're also able to compare this research output to 28 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 57% of its contemporaries.