2018
Huang, P. -J.; Lee, C. -C.; Chiu, L. -Y.; Huang, K. -Y.; Yeh, Y. -M.; Yang, C. -Y.; Chiu, C. -H.; Tang, P.
VAReporter: Variant reporter for cancer research of massive parallel sequencing Journal Article
In: BMC Genomics, 19 , 2018, ISSN: 14712164, (cited By 1).
Abstract | Links | BibTeX | 標籤: Algorithms; Genetic Predisposition to Disease; High-Throughput Nucleotide Sequencing; Humans; Internet; Molecular Sequence Annotation; Mutation; Neoplasms; Precision Medicine; Whole Exome Sequencing; Workflow
@article{Huang2018,
title = {VAReporter: Variant reporter for cancer research of massive parallel sequencing},
author = {P. -J. Huang and C. -C. Lee and L. -Y. Chiu and K. -Y. Huang and Y. -M. Yeh and C. -Y. Yang and C. -H. Chiu and P. Tang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046673650&doi=10.1186%2fs12864-018-4468-5&partnerID=40&md5=9000ef84b6c658f3b994ff25a3b7ce63},
doi = {10.1186/s12864-018-4468-5},
issn = {14712164},
year = {2018},
date = {2018-01-01},
journal = {BMC Genomics},
volume = {19},
publisher = {BioMed Central Ltd.},
abstract = {Background: High throughput sequencing technologies have been an increasingly critical aspect of precision medicine owing to a better identification of disease targets, which contributes to improved health care cost and clinical outcomes. In particular, disease-oriented targeted enrichment sequencing is becoming a widely-accepted application for diagnostic purposes, which can interrogate known diagnostic variants as well as identify novel biomarkers from panels of entire human coding exome or disease-associated genes. Results: We introduce a workflow named VAReporter to facilitate the management of variant assessment in disease-targeted sequencing, the identification of pathogenic variants, the interpretation of biological effects and the prioritization of clinically actionable targets. State-of-art algorithms that account for mutation phenotypes are used to rank the importance of mutated genes through visual analytic strategies. We established an extensive annotation source by integrating a wide variety of biomedical databases and followed the American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation and reporting of sequence variations. Conclusions: In summary, VAReporter is the first web server designed to provide a "one-stop" resource for individual's diagnosis and large-scale cohort studies, and is freely available at http://rnd.cgu.edu.tw/vareporter. © 2018 The Author(s).},
note = {cited By 1},
keywords = {Algorithms; Genetic Predisposition to Disease; High-Throughput Nucleotide Sequencing; Humans; Internet; Molecular Sequence Annotation; Mutation; Neoplasms; Precision Medicine; Whole Exome Sequencing; Workflow},
pubstate = {published},
tppubtype = {article}
}
Background: High throughput sequencing technologies have been an increasingly critical aspect of precision medicine owing to a better identification of disease targets, which contributes to improved health care cost and clinical outcomes. In particular, disease-oriented targeted enrichment sequencing is becoming a widely-accepted application for diagnostic purposes, which can interrogate known diagnostic variants as well as identify novel biomarkers from panels of entire human coding exome or disease-associated genes. Results: We introduce a workflow named VAReporter to facilitate the management of variant assessment in disease-targeted sequencing, the identification of pathogenic variants, the interpretation of biological effects and the prioritization of clinically actionable targets. State-of-art algorithms that account for mutation phenotypes are used to rank the importance of mutated genes through visual analytic strategies. We established an extensive annotation source by integrating a wide variety of biomedical databases and followed the American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation and reporting of sequence variations. Conclusions: In summary, VAReporter is the first web server designed to provide a "one-stop" resource for individual's diagnosis and large-scale cohort studies, and is freely available at http://rnd.cgu.edu.tw/vareporter. © 2018 The Author(s).