TY - JOUR
T1 - SnackVar
T2 - An Open-Source Software for Sanger Sequencing Analysis Optimized for Clinical Use
AU - Kim, Young gon
AU - Kim, Man Jin
AU - Lee, Jee Soo
AU - Lee, Jung Ae
AU - Song, Ji Yun
AU - Cho, Sung Im
AU - Park, Sung Sup
AU - Seong, Moon Woo
N1 - Publisher Copyright:
© 2021 Association for Molecular Pathology and American Society for Investigative Pathology
PY - 2021/2
Y1 - 2021/2
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85100026126
U2 - 10.1016/j.jmoldx.2020.11.001
DO - 10.1016/j.jmoldx.2020.11.001
M3 - Article
C2 - 33246077
AN - SCOPUS:85100026126
SN - 1525-1578
VL - 23
SP - 140
EP - 148
JO - Journal of Molecular Diagnostics
JF - Journal of Molecular Diagnostics
IS - 2
ER -