title: Improved variant calling accuracy by merging replicates in whole-exome sequencing studies.
abstract: In large scale population-based whole-exome sequencing (WES) studies, there are some samples occasionally sequenced two or more times due to a variety of reasons. To investigate how to efficiently utilize these duplicated sequencing data, we conducted comprehensive evaluation of variant calling strategies. 92 samples subjected to WES twice were selected from a large population study. These 92 duplicated samples were divided into two groups: group H consisting of the higher sequencing depth for each subject and group L consisting of the lower depth for each subject. The merged samples for each subject were put in a third group M. Using the GATK multisample toolkit, we compared variant calling accuracy among three strategies. Hierarchical clustering analysis indicated that the two replicates for each subject showed high homogeneity. The comparative analyses on the basis of heterozygous-homozygous ratio (Hete/Homo), transition-transversion ratio (Ti/Tv), and overlapping rate with the 1000 Genomes Project consistently showed that the data quality of the SNPs detected from the M group was more accurate than that of SNPs detected from the H and L groups. These results suggested that merging homogeneous duplicated exomes instead of using one of them could improve variant calling accuracy.
authors.affiliation: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
authors.forename: Yanfeng
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
authors.forename: Bingshan
authors.initials: B
authors.lastname: Li
authors.affiliation: Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
authors.forename: Chun
authors.initials: C
authors.lastname: Li
authors.affiliation: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
authors.forename: Qiuyin
authors.identifier: 0000-0002-9384-5648
authors.initials: Q
authors.lastname: Cai
authors.affiliation: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Zheng
authors.affiliation: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
authors.forename: Jirong
authors.identifier: 0000-0002-7433-9766
authors.initials: J
authors.lastname: Long
mesh_terms: D059472:Exome / Q000235:genetics; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*