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

Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-assoc...

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Autores principales: Shin, JaeMoon, Jeon, Junbeom, Jung, Dawoon, Kim, Kiyong, Kim, Yun Joong, Jeong, Dong-Hoon, Yoon, JeeHee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224645/
https://www.ncbi.nlm.nih.gov/pubmed/35743744
http://dx.doi.org/10.3390/jpm12060959
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author Shin, JaeMoon
Jeon, Junbeom
Jung, Dawoon
Kim, Kiyong
Kim, Yun Joong
Jeong, Dong-Hoon
Yoon, JeeHee
author_facet Shin, JaeMoon
Jeon, Junbeom
Jung, Dawoon
Kim, Kiyong
Kim, Yun Joong
Jeong, Dong-Hoon
Yoon, JeeHee
author_sort Shin, JaeMoon
collection PubMed
description Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, such as whole-genome sequencing, exome sequencing, and gene panel sequencing. Furthermore, patients’ genetic variations related to a specific phenotype can also be identified by analyzing their genomic information. These breakthroughs paved the way for the clinical diagnosis and precise treatment of patients’ diseases. Although many bioinformatics tools have been developed to analyze the genetic variations from the individual patient’s NGS data, it is still challenging to develop user-friendly programs for clinical physicians who do not have bioinformatics programing skills to diagnose a patient’s disease using the genomic data. In response to this demand, we developed a Phenotype to Genotype Variation program (PhenGenVar), which is a user-friendly interface for monitoring the variations in a gene of interest for molecular diagnosis. This allows for flexible filtering and browsing of variants of the disease and phenotype-associated genes. To test this program, we analyzed the whole-genome sequencing data of an anonymous person from the 1000 human genome project data. As a result, we were able to identify several genomic variations, including single-nucleotide polymorphism, insertions, and deletions in specific gene regions. Therefore, PhenGenVar can be used to diagnose a patient’s disease. PhenGenVar is freely accessible and is available at our website.
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spelling pubmed-92246452022-06-24 PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine Shin, JaeMoon Jeon, Junbeom Jung, Dawoon Kim, Kiyong Kim, Yun Joong Jeong, Dong-Hoon Yoon, JeeHee J Pers Med Article Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, such as whole-genome sequencing, exome sequencing, and gene panel sequencing. Furthermore, patients’ genetic variations related to a specific phenotype can also be identified by analyzing their genomic information. These breakthroughs paved the way for the clinical diagnosis and precise treatment of patients’ diseases. Although many bioinformatics tools have been developed to analyze the genetic variations from the individual patient’s NGS data, it is still challenging to develop user-friendly programs for clinical physicians who do not have bioinformatics programing skills to diagnose a patient’s disease using the genomic data. In response to this demand, we developed a Phenotype to Genotype Variation program (PhenGenVar), which is a user-friendly interface for monitoring the variations in a gene of interest for molecular diagnosis. This allows for flexible filtering and browsing of variants of the disease and phenotype-associated genes. To test this program, we analyzed the whole-genome sequencing data of an anonymous person from the 1000 human genome project data. As a result, we were able to identify several genomic variations, including single-nucleotide polymorphism, insertions, and deletions in specific gene regions. Therefore, PhenGenVar can be used to diagnose a patient’s disease. PhenGenVar is freely accessible and is available at our website. MDPI 2022-06-12 /pmc/articles/PMC9224645/ /pubmed/35743744 http://dx.doi.org/10.3390/jpm12060959 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shin, JaeMoon
Jeon, Junbeom
Jung, Dawoon
Kim, Kiyong
Kim, Yun Joong
Jeong, Dong-Hoon
Yoon, JeeHee
PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine
title PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine
title_full PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine
title_fullStr PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine
title_full_unstemmed PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine
title_short PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine
title_sort phengenvar: a user-friendly genetic variant detection and visualization tool for precision medicine
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224645/
https://www.ncbi.nlm.nih.gov/pubmed/35743744
http://dx.doi.org/10.3390/jpm12060959
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