Evidence map›Paper›PMID 29422027›Full record

ArticleBMC bioinformatics2018

OVAS: an open-source variant analysis suite with inheritance modelling.

Monika Mozere, Mehmet Tekman, Jameela Kari, Detlef Bockenhauer, Robert Kleta, Horia Stanescu

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Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Monika MozereDivision of Medicine, University College London, London, NW3 2PF, UK.
Mehmet TekmanDivision of Medicine, University College London, London, NW3 2PF, UK.
Jameela KariPediatric Nephrology Center of Excellence and Pediatric Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
Detlef BockenhauerDivision of Medicine, University College London, London, NW3 2PF, UK.
Robert KletaDivision of Medicine, University College London, London, NW3 2PF, UK. r.kleta@ucl.ac.uk.ORCID 0000-0002-0228-8656
Horia StanescuDivision of Medicine, University College London, London, NW3 2PF, UK.

Funding

European Union FP7 2012-305608
6 · The paper itself

Abstract

backgroundThe 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.

resultsTo 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.

conclusionOVAS 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.

Indexed as

Genetic VariationModels, GeneticSoftwareDatabases, GeneticHumansInheritance PatternsInternetMolecular Sequence AnnotationMutationUser-Computer InterfaceWeb BrowserBootableInheritance modelLive environmentMosaicOpen sourceVariant analysis

Identifiers

PMID29422027
PMCPMC5806474

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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.