CNOGpro: detection and quantification of CNVs in prokaryotic whole-genome sequencing data | Zendy

Ola Brynildsrud | Zendy; Lars-Gustav Snipen | Zendy; Jon Bohlin | Zendy

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CNOGpro: detection and quantification of CNVs in prokaryotic whole-genome sequencing data

Author(s) -

Ola Brynildsrud,

Lars-Gustav Snipen,

Jon Bohlin

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv070

Subject(s) - genome , benchmark (surveying) , computer science , copy number variation , 1000 genomes project , hidden markov model , replicate , computational biology , dna sequencing , whole genome sequencing , biology , data mining , genetics , gene , artificial intelligence , statistics , mathematics , geodesy , genotype , single nucleotide polymorphism , geography

The explosion of whole-genome sequencing (WGS) as a tool in the mapping and understanding of genomes has been accompanied by an equally massive report of tools and pipelines for the analysis of DNA copy number variation (CNV). Most currently available tools are designed specifically for human genomes, with comparatively little literature devoted to CNVs in prokaryotic organisms. However, there are several idiosyncrasies in prokaryotic WGS data. This work proposes a step-by-step approach for detection and quantification of copy number variants specifically aimed at prokaryotes.

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