References
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probabilities. Genome Res. 1998;8(3):186–94.
2. Nielsen R, Paul JS, Albrechtsen A, Song YS. Genotype and SNP calling from next-generation
sequencing data. Nat Rev Genet. 2011;12(6):443–51.
3. Xu C. A review of somatic single nucleotide variant calling algorithms for next-generation
sequencing data. Comput Struct Biotechnol J. 2018;16:15–24.
4. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome
analysis toolkit: a map reduce framework for analyzing next-generation DNA sequencing data.
Genome Res. 2010;20(9):1297–303.
5. Li H. A statistical framework for SNP calling, mutation discovery, association mapping and
population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27
(21):2987–93.
6. You N, Murillo G, Su X, Zeng X, Xu J, Ning K, et al. SNP calling using genotype model selection
on high-throughput sequencing data. Bioinformatics. 2012;28(5):643–50.
7. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, et al. VarScan 2: somatic
mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res.
2012;22(3):568–76.
8. Cai L, Yuan W, Zhang Z, He L, Chou K-C. In-depth comparison of somatic point mutation callers
based on different tumor next-generation sequencing depth data. Sci Rep. 2016;6:36540.
9. Prentice LM, Miller RR, Knaggs J, Mazloomian A, Aguirre Hernandez R, Franchini P, et al.
Formalin fixation increases deamination mutation signature but should not lead to false positive
mutations in clinical practice. PLoS One. 2018;13(4):e0196434.
10. Hayward NK, Wilmott JS, Waddell N, Johansson PA, Field MA, Nones K, et al. Whole-genome
landscapes of major melanoma subtypes. Nature. 2017;545(7653):175–80.
11. Costello M, Pugh TJ, Fennell TJ, Stewart C, Lichtenstein L, Meldrim JC, et al. Discovery and
characterization of artifactual mutations in deep coverage targeted capture sequencing data due to
oxidative DNA damage during sample preparation. Nucleic Acids Res. 2013;41(6):e67.
12. Briggs AW, Stenzel U, Meyer M, Krause J, Kircher M, Pääbo S. Removal of deaminated
cytosines and detection of in vivo methylation in ancient DNA. Nucleic Acids Res. 2010;38(6):
e87.
13. Newman AM, Lovejoy AF, Klass DM, Kurtz DM, Chabon JJ, Scherer F, et al. Integrated digital
error suppression for improved detection of circulating tumor DNA. Nat Biotechnol. 2016;34
(5):547–55.
14. Wang J, Raskin L, Samuels DC, Shyr Y, Guo Y. Genome measures used for quality control are
dependent on gene function and ancestry. Bioinformatics. 2015;31(3):318–23.
15. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of proteincoding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–91.
16. Kosugi S, Momozawa Y, Liu X, Terao C, Kubo M, Kamatani Y. Comprehensive evaluation of
structural variation detection algorithms for whole genome sequencing. Genome Biol. 2019;20
(1):117.
17. Bohannan ZS, Mitrofanova A. Calling variants in the clinic: informed variant calling decisions
based on biological, clinical, and laboratory variables. Comput Struct Biotechnol J. 2019;17:561–
9.
18. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call
format and VCFtools. Bioinformatics. 2011;27(15):2156–8.
19. Danecek P, Nellåker C, McIntyre RE, Buendia-Buendia JE, Bumpstead S, Ponting CP, et al. High
levels of RNA-editing site conservation amongst 15 laboratory mouse strains. Genome Biol.
2012;13(4):26.
10 Identification of Genetic Variants and de novo Mutations Based on NGS
141
1. Ewing B, Green P. Base-calling of automated sequencer traces using Phred. II. Error
probabilities. Genome Res. 1998;8(3):186–94.
2. Nielsen R, Paul JS, Albrechtsen A, Song YS. Genotype and SNP calling from next-generation
sequencing data. Nat Rev Genet. 2011;12(6):443–51.
3. Xu C. A review of somatic single nucleotide variant calling algorithms for next-generation
sequencing data. Comput Struct Biotechnol J. 2018;16:15–24.
4. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome
analysis toolkit: a map reduce framework for analyzing next-generation DNA sequencing data.
Genome Res. 2010;20(9):1297–303.
5. Li H. A statistical framework for SNP calling, mutation discovery, association mapping and
population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27
(21):2987–93.
6. You N, Murillo G, Su X, Zeng X, Xu J, Ning K, et al. SNP calling using genotype model selection
on high-throughput sequencing data. Bioinformatics. 2012;28(5):643–50.
7. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, et al. VarScan 2: somatic
mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res.
2012;22(3):568–76.
8. Cai L, Yuan W, Zhang Z, He L, Chou K-C. In-depth comparison of somatic point mutation callers
based on different tumor next-generation sequencing depth data. Sci Rep. 2016;6:36540.
9. Prentice LM, Miller RR, Knaggs J, Mazloomian A, Aguirre Hernandez R, Franchini P, et al.
Formalin fixation increases deamination mutation signature but should not lead to false positive
mutations in clinical practice. PLoS One. 2018;13(4):e0196434.
10. Hayward NK, Wilmott JS, Waddell N, Johansson PA, Field MA, Nones K, et al. Whole-genome
landscapes of major melanoma subtypes. Nature. 2017;545(7653):175–80.
11. Costello M, Pugh TJ, Fennell TJ, Stewart C, Lichtenstein L, Meldrim JC, et al. Discovery and
characterization of artifactual mutations in deep coverage targeted capture sequencing data due to
oxidative DNA damage during sample preparation. Nucleic Acids Res. 2013;41(6):e67.
12. Briggs AW, Stenzel U, Meyer M, Krause J, Kircher M, Pääbo S. Removal of deaminated
cytosines and detection of in vivo methylation in ancient DNA. Nucleic Acids Res. 2010;38(6):
e87.
13. Newman AM, Lovejoy AF, Klass DM, Kurtz DM, Chabon JJ, Scherer F, et al. Integrated digital
error suppression for improved detection of circulating tumor DNA. Nat Biotechnol. 2016;34
(5):547–55.
14. Wang J, Raskin L, Samuels DC, Shyr Y, Guo Y. Genome measures used for quality control are
dependent on gene function and ancestry. Bioinformatics. 2015;31(3):318–23.
15. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of proteincoding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–91.
16. Kosugi S, Momozawa Y, Liu X, Terao C, Kubo M, Kamatani Y. Comprehensive evaluation of
structural variation detection algorithms for whole genome sequencing. Genome Biol. 2019;20
(1):117.
17. Bohannan ZS, Mitrofanova A. Calling variants in the clinic: informed variant calling decisions
based on biological, clinical, and laboratory variables. Comput Struct Biotechnol J. 2019;17:561–
9.
18. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call
format and VCFtools. Bioinformatics. 2011;27(15):2156–8.
19. Danecek P, Nellåker C, McIntyre RE, Buendia-Buendia JE, Bumpstead S, Ponting CP, et al. High
levels of RNA-editing site conservation amongst 15 laboratory mouse strains. Genome Biol.
2012;13(4):26.
10 Identification of Genetic Variants and de novo Mutations Based on NGS
141