Evidence map›Paper›PMID 35743744›Full record

ArticleJournal of personalized medicine2022

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

JaeMoon Shin, Junbeom Jeon, Dawoon Jung, Kiyong Kim, Yun Joong Kim, Dong-Hoon Jeong, JeeHee Yoon

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

JaeMoon ShinDepartment of Computer Engineering, Hallym University, Chuncheon 24252, Korea.
Junbeom JeonDepartment of Computer Engineering, Hallym University, Chuncheon 24252, Korea.ORCID 0000-0002-3901-3242
Dawoon JungDepartment of Computer Engineering, Hallym University, Chuncheon 24252, Korea.
Kiyong KimDepartment of Electronic Engineering, Kyonggi University, Suwon 16227, Korea.ORCID 0000-0003-3175-8132
Yun Joong KimDepartment of Neurology, Yonsei University College of Medicine, Seoul 03722, Korea.
Dong-Hoon JeongDepartment of Life Science and Multidisciplinary Genome Institute, Hallym University, Chuncheon 24252, Korea.ORCID 0000-0002-2378-1706
JeeHee YoonDepartment of Computer Engineering, Hallym University, Chuncheon 24252, Korea.

Funding

Hallym University Research Fund HRF-202003-020
6 · The paper itself

Abstract

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.

Indexed as

exome browsergenetic variationsNGSprecision medicine

Identifiers

PMID35743744
PMCPMC9224645

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.