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Introducing COCOS: codon consequence scanner for annotating reading frame changes induced by stop-lost and frame shift variants
- Source :
- Bioinformatics
- Publication Year :
- 2017
- Publisher :
- Oxford University Press, 2017.
-
Abstract
- Summary Reading frame altering genomic variants can impact gene expression levels and the structure of protein products, thus potentially inducing disease phenotypes. Current annotation approaches report the impact of such variants in the context of altered DNA sequence only; attributes of the resulting transcript, reading frame and translated protein product are not reported. To remedy this shortcoming, we present a new genetic annotation approach termed Codon Consequence Scanner (COCOS). Implemented as an Ensembl variant effect predictor (VEP) plugin, COCOS captures amino acid sequence alterations stemming from variants that produce an altered reading frame, such as stop-lost variants and small insertions and deletions (InDels). To highlight its significance, COCOS was applied to data from the 1000 Genomes Project. Transcripts affected by stop-lost variants introduce a median of 15 amino acids, while InDels have a more extensive impact with a median of 66 amino acids being incorporated. Captured sequence alterations are written out in FASTA format and can be further analyzed for impact on the underlying protein structure. Availability and Implementation COCOS is available to all users on github: https://github.com/butkiem/COCOS
- Subjects :
- 0301 basic medicine
Statistics and Probability
Reading Frames
Context (language use)
Computational biology
Biology
Biochemistry
DNA sequencing
Frameshift mutation
03 medical and health sciences
INDEL Mutation
Sequence Analysis, Protein
Ensembl
Humans
1000 Genomes Project
Indel
Codon
Frameshift Mutation
Molecular Biology
Peptide sequence
FASTA format
Genomics
Sequence Analysis, DNA
Genome Analysis
Applications Notes
Computer Science Applications
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
Software
Subjects
Details
- Language :
- English
- ISSN :
- 13674811 and 13674803
- Volume :
- 33
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....de9e1195c74f68e721d7a003c30a13eb