Evidence map›Paper›PMID 28185576›Full record

ArticleBMC bioinformatics2016

Var2GO: a web-based tool for gene variants selection.

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

Abstract readEvaluation Study
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ilaria GranataHigh Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy. ilaria.granata@na.icar.cnr.it.
Mara SangiovanniHigh Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy.
Francesco MaioranoHigh Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy.
Marco MieleHigh Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy.
Mario Rosario GuarracinoHigh Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, Napoli, 80131, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOne 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.

resultsHere 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.

conclusionsVar2GO 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.

Indexed as

Genetic VariationComputational BiologyHigh-Throughput Nucleotide SequencingHumansInternetProteinsSoftwareProteinsAnnotationGene ontologyGene variantsNext generation sequencingWeb-based tool

Identifiers

PMID28185576
PMCPMC5123234

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.