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      BrowseVCF: a web-based application and workflow to quickly prioritise disease-causative variants in VCF files.

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      bioRxiv

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          Abstract

          As sequencing costs associated with fast advancing Next Generation Sequencing (NGS) technologies continue to decrease, variant discovery is becoming a more affordable and popular analysis method among research laboratories. Following variant calling and annotation, accurate variant filtering is a crucial step to extract meaningful biological information from sequencing data and to investigate disease etiology. However, the standard variant call file format (VCF) used to store this valuable information is not easy to handle without bioinformatics skills, thus preventing many investigators from directly analysing their data. Here, we present BrowseVCF, an easy-to-use stand-alone software that enables researchers to browse, query and filter millions of variants in a few seconds. Key features include the possibility to store intermediate search results, to query user-defined gene lists, to group samples for family or tumour/normal studies, to download a report of the filters applied, and to export the filtered variants in spreadsheet format. Additionally, BrowseVCF is suitable for any DNA variant analysis (exome, whole-genome and targeted sequencing), can be used also for non-diploid genomes, and is able to discriminate between Single Nucleotide Polymorphisms (SNPs), Insertions/Deletions (InDels), and Multiple Nucleotide Polymorphisms (MNPs). Owing to its portable implementation, BrowseVCF can be used either on personal computers or as part of automated analysis pipelines. The software can be initialised with a few clicks on any operating system without any special administrative or installation permissions. It is actively developed and maintained, and freely available for download from https://github.com/BSGOxford/BrowseVCF/releases/latest.

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          Author and article information

          Journal
          bioRxiv
          December 17 2015
          Article
          10.1101/034769
          76ccdcf8-6ecb-420f-990b-4d78ed69a9ba
          © 2015
          History

          Quantitative & Systems biology,Biophysics
          Quantitative & Systems biology, Biophysics

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