SNP calling using genotype model selection on high-throughput sequencing data

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-calli...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2012-03, Vol.28 (5), p.643-650
Main Authors: You, Na, Murillo, Gabriel, Su, Xiaoquan, Zeng, Xiaowei, Xu, Jian, Ning, Kang, Zhang, Shoudong, Zhu, Jiankang, Cui, Xinping
Format: Article
Language:English
Subjects:
Algorithms
bioinformatics
Biological and medical sciences
computer software
Fundamental and applied biological sciences. Psychology
General aspects
Genomics - methods
genotype
High-Throughput Nucleotide Sequencing
Internet
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Genetic
new methods
Original Papers
Polymorphism, Single Nucleotide
Predictive Value of Tests
single nucleotide polymorphism
Software
Thermoanaerobacter - genetics
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Summary: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 CONTACT: xinping.cui@ucr.edu Supplementary information: Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/bts001