title: On the design and analysis of next-generation sequencing genotyping for a cohort with haplotype-informative reads.
abstract: Next-generation sequencing (NGS) technologies, which can provide base-pair resolution genetic information for all types of genetic variations, are increasingly used in genetics research. However, due to the complex nature of NGS technologies and analytics and their relatively high cost, investigators face practical challenges for both design and analysis. These challenges are further complicated by recent methodological developments that make it possible to use haplotype information in sequencing reads. In light of these developments, we conducted comprehensive simulations to evaluate the effects of sequencing coverage, insert size of paired-end reads, and sample size on genotype calling and haplotype phasing in NGS studies. In contrast to previous studies that typically use idealized scenarios to tease out the effects of individual design and analytic decisions, we used a complete analytical pipeline from read mapping and variant detection to genotype calling and haplotype phasing so that we can assess the joint effects of multiple decisions and thus make more realistic recommendations to investigators. Consistent with previous studies, we found that the use of haplotype information in reads can improve the accuracy of genotype calling and haplotype phasing, and we also found that a mixture of short and long insert sizes of paired-end reads may offer even greater accuracy. However, this benefit is only clear in high coverage sequencing where variant detection is close to perfect. Finally, we observed that LD-based refinement methods do not always outperform single site based methods for genotype calling. Therefore, we should choose analytical methods that are appropriate to the sequencing coverage and sample size in order to use haplotype information in sequencing reads.
authors: Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, United States. Electronic address: dzhi@uab.edu.
authors: Degui
authors: D
authors: Zhi
authors: Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, United States.
authors: Nianjun
authors: N
authors: Liu
authors: Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, United States. Electronic address: kzhang@uab.edu.
authors: Kui
authors: K
authors: Zhang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D014644:Genetic Variation; D005838:Genotype; D060005:Genotyping Techniques; D006239:Haplotypes; D017422:Sequence Analysis, DNA
keywords: Genotype calling; Haplotype; Human genetics; Next-generation sequencing; Resequencing; Simulation; Study design
references: Proc Natl Acad Sci U S A. 2013 Mar 5;110(10):3985-90
references: 23426633
references: Bioinformatics. 2009 Jul 15;25(14):1754-60
references: 19451168
references: Science. 2012 Oct 12;338(6104):222-6
references: 22936568
references: Hum Genet. 2012 Oct;131(10):1555-63
references: 22714655
references: Genet Epidemiol. 2012 Dec;36(8):870-81
references: 22972696
references: Bioinformatics. 2011 Nov 1;27(21):2987-93
references: 21903627
references: Nat Biotechnol. 2009 Sep;27(9):847-50
references: 19668243
references: PLoS Genet. 2009 May;5(5):e1000481
references: 19436704
references: BMC Genomics. 2012 Aug 05;13:375
references: 22863213
references: Nature. 2012 Nov 1;491(7422):56-65
references: 23128226
references: Nat Rev Genet. 2010 Jan;11(1):31-46
references: 19997069
references: Genome Res. 2010 Sep;20(9):1297-303
references: 20644199
references: Nat Rev Genet. 2011 Jun;12(6):443-51
references: 21587300
references: Genet Epidemiol. 2011 May;35(4):269-77
references: 21370254
references: Genet Epidemiol. 2010 Dec;34(8):816-34
references: 21058334
references: Genome Res. 2011 Jun;21(6):952-60
references: 20980557
references: Bioinformatics. 2012 Feb 15;28(4):593-4
references: 22199392
references: Nat Genet. 2011 May;43(5):491-8
references: 21478889
references: Bioinformatics. 2013 Oct 1;29(19):2427-34
references: 23943637
references: Bioinformatics. 2011 Aug 1;27(15):2156-8
references: 21653522
references: Genet Epidemiol. 2011 Sep;35(6):572-9
references: 21618604
references: Nature. 2008 Nov 6;456(7218):53-9
references: 18987734
references: Mol Ecol. 2013 Jun;22(11):3028-35
references: 23174005
references: Genome Res. 2005 Nov;15(11):1576-83
references: 16251467
references: Bioinformatics. 2013 Jan 1;29(1):84-91
references: 23093610
references: Bioinformatics. 2012 Apr 1;28(7):938-46
references: 22285565
references: Nat Biotechnol. 2012 Apr 10;30(4):326-8
references: 22491281
references: PLoS One. 2011;6(8):e23221
references: 21850262
references: Nat Rev Genet. 2014 Feb;15(2):121-32
references: 24434847
references: PLoS One. 2013 Nov 18;8(11):e79667
references: 24260275
references: Bioinformatics. 2009 Aug 15;25(16):2078-9
references: 19505943
references: Nat Genet. 2012 May 20;44(6):631-5
references: 22610117
references: Bioinformatics. 2011 Apr 15;27(8):1157-8
references: 21320865
references: Genet Epidemiol. 2010 Jul;34(5):479-91
references: 20552648
references: Am J Hum Genet. 2013 Oct 3;93(4):687-96
references: 24094745