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OVAS: an open-source variant analysis suite with inheritance modelling.
Mozere, Monika; Tekman, Mehmet; Kari, Jameela; Bockenhauer, Detlef; Kleta, Robert; Stanescu, Horia.
Afiliação
  • Mozere M; Division of Medicine, University College London, London, NW3 2PF, UK.
  • Tekman M; Division of Medicine, University College London, London, NW3 2PF, UK.
  • Kari J; Pediatric Nephrology Center of Excellence and Pediatric Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
  • Bockenhauer D; Division of Medicine, University College London, London, NW3 2PF, UK.
  • Kleta R; Division of Medicine, University College London, London, NW3 2PF, UK. r.kleta@ucl.ac.uk.
  • Stanescu H; Division of Medicine, University College London, London, NW3 2PF, UK.
BMC Bioinformatics ; 19(1): 46, 2018 02 08.
Article em En | MEDLINE | ID: mdl-29422027
ABSTRACT

BACKGROUND:

The advent of modern high-throughput genetics continually broadens the gap between the rising volume of sequencing data, and the tools required to process them. The need to pinpoint a small subset of functionally important variants has now shifted towards identifying the critical differences between normal variants and disease-causing ones. The ever-increasing reliance on cloud-based services for sequence analysis and the non-transparent methods they utilize has prompted the need for more in-situ services that can provide a safer and more accessible environment to process patient data, especially in circumstances where continuous internet usage is limited.

RESULTS:

To address these issues, we herein propose our standalone Open-source Variant Analysis Sequencing (OVAS) pipeline; consisting of three key stages of processing that pertain to the separate modes of annotation, filtering, and interpretation. Core annotation performs variant-mapping to gene-isoforms at the exon/intron level, append functional data pertaining the type of variant mutation, and determine hetero/homozygosity. An extensive inheritance-modelling module in conjunction with 11 other filtering components can be used in sequence ranging from single quality control to multi-file penetrance model specifics such as X-linked recessive or mosaicism. Depending on the type of interpretation required, additional annotation is performed to identify organ specificity through gene expression and protein domains. In the course of this paper we analysed an autosomal recessive case study. OVAS made effective use of the filtering modules to recapitulate the results of the study by identifying the prescribed compound-heterozygous disease pattern from exome-capture sequence input samples.

CONCLUSION:

OVAS is an offline open-source modular-driven analysis environment designed to annotate and extract useful variants from Variant Call Format (VCF) files, and process them under an inheritance context through a top-down filtering schema of swappable modules, run entirely off a live bootable medium and accessed locally through a web-browser.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Variação Genética / Software / Padrões de Herança / Modelos Genéticos Limite: Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Variação Genética / Software / Padrões de Herança / Modelos Genéticos Limite: Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido