Evidence map›Paper›PMID 35965322›Full record

ArticleCell & bioscience2022

OpenVar: functional annotation of variants in non-canonical open reading frames.

Marie A Brunet, Sébastien Leblanc, Xavier Roucou

Open access · goldAbstract read
In one paragraph

Article in Cell & bioscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 28% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

3 authors at 1 institution in 1 country.

Marie A BrunetDepartment of Pediatrics, Medical Genetics Service, Université de Sherbrooke, 3201 Jean Mignault, Sherbrooke, QC, J1E 4K8, Canada. marie.brunet@usherbrooke.ca.ORCID http://orcid.org/0000-0001-5973-3522
Sébastien LeblancDepartment of Biochemistry and Functional Genomics, Université de Sherbrooke, 3201 Jean Mignault, Sherbrooke, QC, J1E 4K8, Canada.
Xavier RoucouCentre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CRCHUS), Sherbrooke, QC, Canada. xavier.roucou@usherbrooke.ca.ORCID http://orcid.org/0000-0001-9370-5584
Université de Sherbrooke · CA

Funding

Canada Research Chairs ChairCIHR PJT-175322Fonds de Recherche du Québec - Santé Junior 1Fonds de Recherche du Québec - Santé Scholarship
6 · The paper itself

Abstract

backgroundRecent technological advances have revealed thousands of functional open reading frames (ORF) that have eluded reference genome annotations. These overlooked ORFs are found throughout the genome, in any reading frame of transcripts, mature or non-coding, and can overlap annotated ORFs in a different reading frame. The exploration of these novel ORFs in genomic datasets and of their role in genetic traits is hindered by a lack of software.

resultsHere, we present OpenVar, a genomic variant annotator that mends that gap and fosters meaningful discoveries. To illustrate the potential of OpenVar, we analysed all variants within SynMicDB, a database of cancer-associated synonymous mutations. By including non-canonical ORFs in the analysis, OpenVar yields a 33.6-fold, 13.8-fold and 8.3-fold increase in high impact variants over Annovar, SnpEff and VEP respectively. We highlighted an overlapping non-canonical ORF in the HEY2 gene where variants significantly clustered.

conclusionsOpenVar integrates non-canonical ORFs in the analysis of genomic variants, unveiling new research avenues to better understand the genotype-phenotype relationships.

Indexed as

Alternative ORFGenomeNGSOpenProtSmall ORFSNPVariant annotation

Identifiers

PMID35965322
PMCPMC9375913
OpenAlexW4291291776

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.