Comprehensive analysis to improve the validation rate for single nucleotide variants detected by next-generation sequencing.
Next-generation sequencing (NGS) has enabled the high-throughput discovery of germline and somatic mutations. However, NGS-based variant detection is still prone to errors, resulting in inaccurate variant calls. Here, we categorized the variants detected by NGS according to total read depth (TD) and SNP quality (SNPQ), and performed Sanger sequencing with 348 selected non-synonymous single nucleotide variants (SNVs) for validation. Using the SAMtools and GATK algorithms, the validation rate was positively correlated with SNPQ but showed no correlation with TD. In addition, common variants called by both programs had a higher validation rate than caller-specific variants. We further examined several parameters to improve the validation rate, and found that strand bias (SB) was a key parameter. SB in NGS data showed a strong difference between the variants passing validation and those that failed validation, showing a validation rate of more than 92% (filtering cutoff value: alternate allele forward [AF] ≥ 20 and AF<80 in SAMtools, SB<-10 in GATK). Moreover, the validation rate increased significantly (up to 97-99%) when the variant was filtered together with the suggested values of mapping quality (MQ), SNPQ and SB. This detailed and systematic study provides comprehensive recommendations for improving validation rates, saving time and lowering cost in NGS analyses.
Division of Intractable Diseases, Center for Biomedical Sciences, National Institute of Health, Chungcheongbuk-do, South Korea.
Mi-Hyun
MH
Park
Macrogen Inc., Gasan-dong, Seoul, South Korea.
Hwanseok
H
Rhee
Macrogen Inc., Gasan-dong, Seoul, South Korea.
Jung Hoon
JH
Park
Division of Intractable Diseases, Center for Biomedical Sciences, National Institute of Health, Chungcheongbuk-do, South Korea.
Hae-Mi
HM
Woo
Department of Neurology, Samsung Medical Center, Sungkyunkwan University, School of Medicine, Seoul, South Korea.
Byung-Ok
BO
Choi
Division of Intractable Diseases, Center for Biomedical Sciences, National Institute of Health, Chungcheongbuk-do, South Korea.
Bo-Young
BY
Kim
Department of Biological Science, Kongju National University, Gongju, South Korea.
Ki Wha
KW
Chung
Department of Biological Sciences, KAIST, Yuseong-gu, Daejeon, South Korea.
Yoo-Bok
YB
Cho
Division of Intractable Diseases, Center for Biomedical Sciences, National Institute of Health, Chungcheongbuk-do, South Korea.
Hyung Jin
HJ
Kim
Division of Intractable Diseases, Center for Biomedical Sciences, National Institute of Health, Chungcheongbuk-do, South Korea.
Ji-Won
JW
Jung
Division of Intractable Diseases, Center for Biomedical Sciences, National Institute of Health, Chungcheongbuk-do, South Korea.
Soo Kyung
SK
Koo
D000465:Algorithms; D002607:Charcot-Marie-Tooth Disease / Q000235:genetics*; D059472:Exome; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D020641:Polymorphism, Single Nucleotide