ArticleNucleic acids research2009
Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation.
Article in Nucleic acids research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A Single-Array-Based Method for Detecting Copy Number Variants Using Affymetrix High Density SNP Arrays and its Application to Breast Cancer.Cancer informatics · 2014Article
- An imputation approach for oligonucleotide microarrays.PloS one · 2013Article
- Hybridization and amplification rate correction for affymetrix SNP arrays.BMC medical genomics · 2012Article
- Estimation of parent specific DNA copy number in tumors using high-density genotyping arrays.PLoS computational biology · 2011Article
- Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology.The Journal of nutritional biochemistry · 2010Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms.
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Registered trials
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