Literature DB >> 33246077

SnackVar: An Open-Source Software for Sanger Sequencing Analysis Optimized for Clinical Use.

Young-Gon Kim1, Man Jin Kim1, Jee-Soo Lee1, Jung Ae Lee1, Ji Yun Song1, Sung Im Cho1, Sung-Sup Park1, Moon-Woo Seong2.   

Abstract

Despite the wide application of next-generation sequencing, Sanger sequencing still plays a necessary role in clinical laboratories. However, recent developments in the field of bioinformatics have focused mostly on next-generation sequencing, while tools for Sanger sequencing have shown little progress. In this study, SnackVar (https://github.com/Young-gonKim/SnackVar, last accessed June 22, 2020), a novel graphical user interface-based software for Sanger sequencing, was developed. All types of variants, including heterozygous insertion/deletion variants, can be identified by SnackVar with minimal user effort. The featured reference sequences of all of the genes are prestored in SnackVar, allowing for detected variants to be precisely described based on coding DNA references according to the nomenclature of the Human Genome Variation Society. Among 88 previously reported variants from four insertion/deletion-rich genes (BRCA1, APC, CALR, and CEBPA), the result of SnackVar agreed with reported results in 87 variants [98.9% (93.0%; 99.9%)]. The cause of one incorrect variant calling was proven to be erroneous base callings from poor-quality trace files. Compared with commercial software, SnackVar required less than one-half of the time taken for the analysis of a selected set of test cases. We expect SnackVar to be a cost-effective option for clinical laboratories performing Sanger sequencing.
Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2020        PMID: 33246077     DOI: 10.1016/j.jmoldx.2020.11.001

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  2 in total

1.  SnackNTM: An Open-Source Software for Sanger Sequencing-based Identification of Nontuberculous Mycobacterial Species.

Authors:  Young-Gon Kim; Kiwook Jung; Seunghwan Kim; Man Jin Kim; Jee-Soo Lee; Sung-Sup Park; Moon-Woo Seong
Journal:  Ann Lab Med       Date:  2022-03-01       Impact factor: 3.464

2.  Direct Detection of Antibiotic Resistance in Chinese Helicobacter pylori Clinical Isolates by Sequencing-Based Approach.

Authors:  Lixia Tian; Yi Yao; Li Yin; Lanxiang Wang; Ze An; Lin Kang; Chenglin Ru; Jinping Li
Journal:  J Healthc Eng       Date:  2022-04-15       Impact factor: 3.822

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.