Literature DB >> 29036298

myVCF: a desktop application for high-throughput mutations data management.

Alessandro Pietrelli1,2, Luca Valenti1,3.   

Abstract

SUMMARY: 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.
AVAILABILITY AND IMPLEMENTATION: https://apietrelli.github.io/myVCF/. CONTACT: pietrelli@ingm.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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Year:  2017        PMID: 29036298     DOI: 10.1093/bioinformatics/btx475

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine.

Authors:  JaeMoon Shin; Junbeom Jeon; Dawoon Jung; Kiyong Kim; Yun Joong Kim; Dong-Hoon Jeong; JeeHee Yoon
Journal:  J Pers Med       Date:  2022-06-12

2.  VCF-Server: A web-based visualization tool for high-throughput variant data mining and management.

Authors:  Jianping Jiang; Jianlei Gu; Tingting Zhao; Hui Lu
Journal:  Mol Genet Genomic Med       Date:  2019-05-24       Impact factor: 2.183

Review 3.  Comprehensive Outline of Whole Exome Sequencing Data Analysis Tools Available in Clinical Oncology.

Authors:  Áron Bartha; Balázs Győrffy
Journal:  Cancers (Basel)       Date:  2019-11-04       Impact factor: 6.639

  3 in total

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