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

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

doi:10.1186/s12859-018-2030-8

Monika Mozere, Robert Kleta + Show 4 more

Open Access

https://doi.org/10.1186/s12859-018-2030-8

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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.

Highlights

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 raw sequence FASTQ reads produced by these high-throughput sequencing (HTS) platforms are aligned to a specific version of the NCBI reference sequence and collated into a Binary Alignment Map (BAM) where variants of interest can be individually “called” to form a Variant Call Format (VCF) file of novel or known variants conforming to a specific variant database [5, 17]
First case study Three families presented with hyperinsulinemic hypoglycemia and congenital polycystic kidney disease (HIPKD), a rare newly discovered disorder following an autosomal recessive model

Summary

Introduction

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. Modern high-throughput sequencing (HTS) approaches post-Sanger era have superseded this standard, allowing for a greater number of variants to be sequenced across the whole genome by employing powerful mass. The raw sequence FASTQ reads produced by these HTS platforms are aligned to a specific version of the NCBI reference sequence and collated into a Binary Alignment Map (BAM) where variants of interest can be individually “called” to form a Variant Call Format (VCF) file of novel or known variants conforming to a specific variant database (dbSNP) [5, 17]. The VCF specification was designed for the 1000 Genomes project to produce a robust format that could house the many samples often sequenced under the same batch, but has since been adopted by projects such as UK10K, dbSNP, NHLBI Exome Project, amongst others. Major and minor alleles are specific only to the sample population but their frequencies can be pre-computed and appended to a variant line as additional information to be utilized in small population analyses such as inheritance modelling [5]

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