SNP detection for massively parallel whole-genome resequencing

Li, Ruiqiang, Li, Yingrui, Fang, Xiaodong, Yang, Huanming, Wang, Jian, Kristiansen, Karsten and Wang, Jun (2009) SNP detection for massively parallel whole-genome resequencing. Genome Research, 19 6: 1124-1132. doi:10.1101/gr.088013.108

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Author Li, Ruiqiang
Li, Yingrui
Fang, Xiaodong
Yang, Huanming
Wang, Jian
Kristiansen, Karsten
Wang, Jun
Title SNP detection for massively parallel whole-genome resequencing
Journal name Genome Research   Check publisher's open access policy
ISSN 1088-9051
Publication date 2009-01-01
Year available 2009
Sub-type Article (original research)
DOI 10.1101/gr.088013.108
Open Access Status File (Publisher version)
Volume 19
Issue 6
Start page 1124
End page 1132
Total pages 9
Place of publication Cold Spring Harbor, NY United States
Publisher Cold Spring Harbor Laboratory Press
Language eng
Abstract Next-generation massively parallel sequencing technologies provide ultrahigh throughput at two orders of magnitude lower unit cost than capillary Sanger sequencing technology. One of the key applications of next-generation sequencing is studying genetic variation between individuals using whole-genome or target region resequencing. Here, we have developed a consensus-calling and SNP-detection method for sequencing-by-synthesis Illumina Genome Analyzer technology. We designed this method by carefully considering the data quality, alignment, and experimental errors common to this technology. All of this information was integrated into a single quality score for each base under Bayesian theory to measure the accuracy of consensus calling. We tested this methodology using a large-scale human resequencing data set of 363coverage and assembled a high-quality nonrepetitive consensus sequence for 92.25% of the diploid autosomes and 88.07% of the haploid X chromosome. Comparison of the consensus sequence with Illumina human 1M BeadChip genotyped alleles from the same DNA sample showed that 98.6% of the 37,933 genotyped alleles on the X chromosome and 98% of 999,981 genotyped alleles on autosomes were covered at 99.97% and 99.84% consistency, respectively. At a low sequencing depth, we used prior probability of dbSNP alleles and were able to improve coverage of the dbSNP sites significantly as compared to that obtained using a nonimputation model. Our analyses demonstrate that our method has a very low false call rate at any sequencing depth and excellent genome coverage at a high sequencing depth.
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Document type: Journal Article
Sub-type: Article (original research)
Collection: Institute for Molecular Bioscience - Publications
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Created: Fri, 04 Sep 2015, 22:16:58 EST by Mr Mathew Carter on behalf of Institute for Molecular Bioscience