ArticleBioinformatics (Oxford, England)2013
PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 6 citations in OpenAlex.
- An Integrated Approach for RNA-seq Data Normalization.Cancer informatics · 2016Article
- Impact of centralization on aCGH-based genomic profiles for precision medicine in oncology.Annals of oncology : official journal of the European Society for Medical Oncology · 2015Article
- BCRgt: a Bayesian cluster regression-based genotyping algorithm for the samples with copy number alterations.BMC bioinformatics · 2014Article
- Beta approximation of ratio distribution and its application to next generation sequencing read counts.Journal of applied statisticsArticle
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Authors and funding
4 authors at 3 institutions in 1 country.
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Abstract
motivationNormalization is critical in DNA copy number analysis. We propose a new method to correctly identify two-copy probes from the genome to obtain representative references for normalization in single nucleotide polymorphism arrays. The method is based on a two-state Hidden Markov Model. Unlike most currently available methods in the literature, the proposed method does not need to assume that the percentage of two-copy state probes is dominant in the genome, as long as there do exist two-copy probes.
resultsThe real data analysis and simulation study show that the proposed algorithm is successful in that (i) it performs as well as the current methods (e.g. CGHnormaliter and popLowess) for samples with dominant two-copy states and outperforms these methods for samples with less dominant two-copy states; (ii) it can identify the copy-neutral loss of heterozygosity; and (iii) it is efficient in terms of the computational time used. AVAILABILITY: R scripts are available at http://publichealth.lsuhsc.edu/PAIR.html.
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