PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays
Author(s) -
Shengping Yang,
Stanley Pounds,
Kun Zhang,
Zhide Fang
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts683
Subject(s) - normalization (sociology) , loss of heterozygosity , computer science , scripting language , snp , genome , hidden markov model , copy number variation , computational biology , single nucleotide polymorphism , algorithm , genetics , biology , artificial intelligence , allele , gene , operating system , sociology , anthropology , genotype
Normalization 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.
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