MOTIVATION: A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base-calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for. RESULTS: A novel method of consensus and SNP calling, Genotype Model Selection (GeMS), is given which accounts for the errors that occur during the preparation of the genomic sample. Simulations and real data analyses indicate that GeMS has the best performance balance of sensitivity and positive predictive value among the tested SNP callers. AVAILABILITY: The GeMS package can be downloaded from https://sites.google.com/a/bioinformatics.ucr.edu/xinping-cui/home/software or http://computationalbioenergy.org/software.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base-calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for. RESULTS: A novel method of consensus and SNP calling, Genotype Model Selection (GeMS), is given which accounts for the errors that occur during the preparation of the genomic sample. Simulations and real data analyses indicate that GeMS has the best performance balance of sensitivity and positive predictive value among the tested SNP callers. AVAILABILITY: The GeMS package can be downloaded from https://sites.google.com/a/bioinformatics.ucr.edu/xinping-cui/home/software or http://computationalbioenergy.org/software.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: G T Marth; I Korf; M D Yandell; R T Yeh; Z Gu; H Zakeri; N O Stitziel; L Hillier; P Y Kwok; W R Gish Journal: Nat Genet Date: 1999-12 Impact factor: 38.330
Authors: Yufeng Shen; Zhengzheng Wan; Cristian Coarfa; Rafal Drabek; Lei Chen; Elizabeth A Ostrowski; Yue Liu; George M Weinstock; David A Wheeler; Richard A Gibbs; Fuli Yu Journal: Genome Res Date: 2009-12-17 Impact factor: 9.043
Authors: Daniel C Koboldt; Ken Chen; Todd Wylie; David E Larson; Michael D McLellan; Elaine R Mardis; George M Weinstock; Richard K Wilson; Li Ding Journal: Bioinformatics Date: 2009-06-19 Impact factor: 6.937
Authors: Gabriel H Murillo; Na You; Xiaoquan Su; Wei Cui; Muredach P Reilly; Mingyao Li; Kang Ning; Xinping Cui Journal: Bioinformatics Date: 2016-01-18 Impact factor: 6.937