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Myvcf: A Desktop Application For High-Throughput Mutations Data Management

Authors: Pietrelli Alessandro;

Myvcf: A Desktop Application For High-Throughput Mutations Data Management

Abstract

Next-generation sequencing technologies have become the most powerful tool to discover genetic variants associated with human diseases. Although the dramatic reductions in the costs facilitate the use in the wet-lab and clinics, the huge amount of data generated renders their management by non-expert researchers and physicians extremely difficult. Therefore, there is an urgent need of novel approaches and tools aimed at getting the ‘end-users’ closer to the sequencing data, facilitating the access by non-bioinformaticians, and to speed-up the functional interpretation of genetic variants. We developed myVCF, a standalone, easy-to-use desktop application, which is based on a browser interface and is suitable for Windows, Mac and UNIX systems. myVCF is an efficient platform that is able to manage multiple sequencing projects created from VCF files within the system; stores genetic variants and samples genotypes from an annotated VCF files into a SQLite database; implements a flexible search engine for data exploration, allowing to query for chromosomal region, gene, single variant or dbSNP ID. Besides, myVCF generates a summary statistics report about mutations distribution across samples and across the genome/exome by aggregating the information within the VCF file. In summary, the myVCF platform allows end-users without strong programming and bioinformatics skills to explore, query, visualize and export mutations data in a simple and straightforward way.

Keywords

FOS: Computer and information sciences, Bioinformatics, Genomics, Data managment

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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