| Autor: |
Marie A. Brunet, Sébastien Leblanc, Xavier Roucou |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Cell & Bioscience, Vol 12, Iss 1, Pp 1-7 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2045-3701 |
| DOI: |
10.1186/s13578-022-00871-x |
| Popis: |
Abstract Background Recent 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. Results Here, 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. Conclusions OpenVar integrates non-canonical ORFs in the analysis of genomic variants, unveiling new research avenues to better understand the genotype–phenotype relationships. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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