Literature DB >> 15657097

Dynamic model based algorithms for screening and genotyping over 100 K SNPs on oligonucleotide microarrays.

Xiaojun Di1, Hajime Matsuzaki, Teresa A Webster, Earl Hubbell, Guoying Liu, Shoulian Dong, Dan Bartell, Jing Huang, Richard Chiles, Geoffrey Yang, Mei-mei Shen, David Kulp, Giulia C Kennedy, Rui Mei, Keith W Jones, Simon Cawley.   

Abstract

MOTIVATION: A high density of single nucleotide polymorphism (SNP) coverage on the genome is desirable and often an essential requirement for population genetics studies. Region-specific or chromosome-specific linkage studies also benefit from the availability of as many high quality SNPs as possible. The availability of millions of SNPs from both Perlegen and the public domain and the development of an efficient microarray-based assay for genotyping SNPs has brought up some interesting analytical challenges. Effective methods for the selection of optimal subsets of SNPs spanning the genome and methods for accurately calling genotypes from probe hybridization patterns have enabled the development of a new microarray-based system for robustly genotyping over 100,000 SNPs per sample.
RESULTS: We introduce a new dynamic model-based algorithm (DM) for screening over 3 million SNPs and genotyping over 100,000 SNPs. The model is based on four possible underlying states: Null, A, AB and B for each probe quartet. We calculate a probe-level log likelihood for each model and then select between the four competing models with an SNP-level statistical aggregation across multiple probe quartets to provide a high-quality genotype call along with a quality measure of the call. We assess performance with HapMap reference genotypes, informative Mendelian inheritance relationship in families, and consistency between DM and another genotype classification method. At a call rate of 95.91% the concordance with reference genotypes from the HapMap Project is 99.81% based on over 1.5 million genotypes, the Mendelian error rate is 0.018% based on 10 trios, and the consistency between DM and MPAM is 99.90% at a comparable rate of 97.18%. We also develop methods for SNP selection and optimal probe selection. AVAILABILITY: The DM algorithm is available in Affymetrix's Genotyping Tools software package and in Affymetrix's GDAS software package. See http://www.affymetrix.com for further information. 10 K and 100 K mapping array data are available on the Affymetrix website.

Entities:  

Mesh:

Year:  2005        PMID: 15657097     DOI: 10.1093/bioinformatics/bti275

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  93 in total

1.  Microarray analysis of copy number variation in single cells.

Authors:  Peter Konings; Evelyne Vanneste; Sigrun Jackmaert; Michèle Ampe; Geert Verbeke; Yves Moreau; Joris Robert Vermeesch; Thierry Voet
Journal:  Nat Protoc       Date:  2012-01-19       Impact factor: 13.491

2.  SNP array-based copy number and genotype analyses for preimplantation genetic diagnosis of human unbalanced translocations.

Authors:  Chris M J van Uum; Servi J C Stevens; Joseph C F M Dreesen; Marion Drüsedau; Hubert J Smeets; Bertien Hollanders-Crombach; Christine E M de Die-Smulders; Joep P M Geraedts; John J M Engelen; Edith Coonen
Journal:  Eur J Hum Genet       Date:  2012-02-29       Impact factor: 4.246

3.  Biological pathway-based genome-wide association analysis identified the vasoactive intestinal peptide (VIP) pathway important for obesity.

Authors:  Yong-Jun Liu; Yan-Fang Guo; Li-Shu Zhang; Yu-Fang Pei; Na Yu; Ping Yu; Christopher J Papasian; Hong-Wen Deng
Journal:  Obesity (Silver Spring)       Date:  2010-04-08       Impact factor: 5.002

4.  Evaluating variations of genotype calling: a potential source of spurious associations in genome-wide association studies.

Authors:  Huixiao Hong; Zhenqiang Su; Weigong Ge; Leming Shi; Roger Perkins; Hong Fang; Donna Mendrick; Weida Tong
Journal:  J Genet       Date:  2010-04       Impact factor: 1.166

5.  A whole-genome scan in a large family with leukodystrophy and oligodontia reveals linkage to 10q22.

Authors:  Eliane Chouery; Valérie Delague; Nadine Jalkh; Nabiha Salem; Jessy Kfoury; Diana Rodriguez; Brigitte Chabrol; Odile Boespflug-Tanguy; Nicolas Lévy; Jean Louis Serre; André Mégarbané
Journal:  Neurogenetics       Date:  2010-08-19       Impact factor: 2.660

Review 6.  Genomic platforms for cancer research: potential diagnostic and prognostic applications in clinical oncology.

Authors:  Pedro Jares; Elías Campo
Journal:  Clin Transl Oncol       Date:  2006-03       Impact factor: 3.405

7.  Genome-wide copy-number-variation study identified a susceptibility gene, UGT2B17, for osteoporosis.

Authors:  Tie-Lin Yang; Xiang-Ding Chen; Yan Guo; Shu-Feng Lei; Jin-Tang Wang; Qi Zhou; Feng Pan; Yuan Chen; Zhi-Xin Zhang; Shan-Shan Dong; Xiang-Hong Xu; Han Yan; Xiaogang Liu; Chuan Qiu; Xue-Zhen Zhu; Teng Chen; Meng Li; Hong Zhang; Liang Zhang; Betty M Drees; James J Hamilton; Christopher J Papasian; Robert R Recker; Xiao-Ping Song; Jing Cheng; Hong-Wen Deng
Journal:  Am J Hum Genet       Date:  2008-11-06       Impact factor: 11.025

8.  Modeling Informatively Missing Genotypes in Haplotype Analysis.

Authors:  Nianjun Liu; Richard Bucala; Hongyu Zhao
Journal:  Commun Stat Theory Methods       Date:  2009       Impact factor: 0.893

9.  Late-onset Charcot-Marie-Tooth disease 4F caused by periaxin gene mutation.

Authors:  Shoko Tokunaga; Akihiro Hashiguchi; Akiko Yoshimura; Kengo Maeda; Takashi Suzuki; Hiroyo Haruki; Tomonori Nakamura; Yuji Okamoto; Hiroshi Takashima
Journal:  Neurogenetics       Date:  2012-08-01       Impact factor: 2.660

10.  Detection of mutant NPM1 mRNA in acute myeloid leukemia using custom gene expression arrays.

Authors:  Martin H van Vliet; Belinda Dumee; Erik Simons; Lars Bullinger; Konstanze Döhner; Hartmut Döhner; Henk Viëtor; Bob Löwenberg; Peter J M Valk; Erik H van Beers
Journal:  Genet Test Mol Biomarkers       Date:  2013-04
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.