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Var2GO: a web-based tool for gene variants selection

Overview of attention for article published in BMC Bioinformatics, November 2016
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Title
Var2GO: a web-based tool for gene variants selection
Published in
BMC Bioinformatics, November 2016
DOI 10.1186/s12859-016-1197-0
Pubmed ID
Authors

Ilaria Granata, Mara Sangiovanni, Francesco Maiorano, Marco Miele, Mario Rosario Guarracino

Abstract

One of the most challenging issue in the variant calling process is handling the resulting data, and filtering the genes retaining only the ones strictly related to the topic of interest. Several tools permit to gather annotations at different levels of complexity for the detected genes and to group them according to the pathways and/or processes they belong to. However, it might be a time consuming and frustrating task. This is partly due to the size of the file, that might contain many thousands of genes, and to the search of associated variants that requires a gene-by-gene investigation and annotation approach. As a consequence, the initial gene list is often reduced exploiting the knowledge of variants effect, novelty and genotype, with the potential risk of losing meaningful pieces of information. Here we present Var2GO, a new web-based tool to support the annotation and filtering of variants and genes coming from variant calling of high-throughput sequencing data. Var2GO permits to upload either the unprocessed Variant Calling Format file or a table containing the annotated variants. The raw data undergo a preliminary step of variants annotation, using the SnpEff tool, and are converted to a table format. The table is then uploaded into an on the fly generated database. Genes associated to the variants are automatically annotated with the corresponding Gene Ontology terms covering the three GO domains. Using the web interface it is then possible to filter and extract, from the whole list, genes having annotations in the domain of interest, by simply specifying filtering parameters and one or more keywords. The relevance of this tool is demonstrated on exome sequencing data. Var2GO is a novel tool that implements a topic-based approach, expressly designed to help biologists in narrowing the search of relevant genes coming from variant calling analysis. Its main purpose is to support non-bioinformaticians in handling and processing raw variant calling data through an intuitive web interface. Furthermore, Var2GO offers a complete pipeline that, starting from the raw VCF file, allows to annotate both variants and associated genes and supports the extraction of relevant biological knowledge.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 37%
Student > Postgraduate 3 16%
Student > Ph. D. Student 2 11%
Student > Doctoral Student 1 5%
Student > Bachelor 1 5%
Other 3 16%
Unknown 2 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 37%
Agricultural and Biological Sciences 6 32%
Unspecified 1 5%
Computer Science 1 5%
Immunology and Microbiology 1 5%
Other 0 0%
Unknown 3 16%
Attention Score in Context

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 13 February 2017.
All research outputs
#18,531,724
of 22,953,506 outputs
Outputs from BMC Bioinformatics
#6,341
of 7,308 outputs
Outputs of similar age
#237,418
of 313,320 outputs
Outputs of similar age from BMC Bioinformatics
#88
of 125 outputs
Altmetric has tracked 22,953,506 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 7,308 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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We're also able to compare this research output to 125 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.